the contribution of knowledge management to project...

THE CONTRIBUTION OF KNOWLEDGE MANAGEMENT TO PROJECT MANAGEMENT

PERFORMANCE IN ENGINEERING PROJECT-BASED ORGANISATIONS

NEE TECK SOON

MASTER OF BUSINESS ADMINISTRATION

UNIVERSITI TUNKU ABDUL RAHMAN

FACULTY OF ACCOUNTANCY AND MANAGEMENT

DECEMBER 2015

The Contribution of Knowledge Management to Project Management Performance in Engineering Project-Based

Organisations

Nee Teck Soon

A research project submitted in partial fulfilment of the

requirement for the degree of

Master of Business Administration

Universiti Tunku Abdul Rahman

Faculty of Accountancy and Management

December 2015

The Contribution of Knowledge Management to Project Management Performance in Engineering Project-Based

Organisations

By

Nee Teck Soon

This research project is supervised by

Dr Hen Kai Wah Assistant Professor

Department of International Business Faculty of Accountancy and Management

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Copyright @ 2015 ALL RIGHTS RESERVED. No part of this paper may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, graphic, electronic, mechanical, photocopying, recording, scanning, or otherwise, without the prior consent of the authors.

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DECLARATION

I hereby declare that: (1) This Research Project is the end result of my own work and that due acknowledgement

has been given in the references to all sources of information be they printed, electronic, or personal.

(2) No portion of this research project has been submitted in support of any application for

any other degree or qualification of this or any other university, or other institutes of learning.

(3) The word count of this research report is 18364. Name of Student: Nee Teck Soon Student ID: 11UKM05998 Signature: _____________________ Date: 10 Dec 2015

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ACKNOWLEDGEMENTS

I would like to express my deep sense of gratitude to my final year project supervisor, Dr

Hen Kai Wah and PMI, Malaysia secretary, Mr Ng Kian Hoe, without whom I could not

have successful journey to complete this final year project. Dr Hen was very

instrumental in motivating me to take knowledge management scope as my final year

project topic. He provided excellent guidance and authoritative support on the project

topic, which required the mastery of knowledge from two subject areas of study,

knowledge management and project management. The coaching and mentoring I had

received during the early part of my project was very valuable and helped me to further

hone my research skills.

Besides that, I would like to thank Mr Ng for his time and effort to provide me a list of

contacts for project management personnel registered with PMI, Malaysia. This contact

list provided me a group of sample for conducting survey questionnaire for my final year

project. Additionally, I would like to express my appreciation to my survey respondents.

Finally, I would also like to owe my special gratitude to UTAR, FAM and IPSR staffs,

who helped me on the journey of this final year project.

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TABLE OF CONTENTS Page Copyright Page ………………………………………………………………… I Declaration …………………………………………………………………….. II Acknowledgements ……………………………………………………………. III Table of Contents ……………………………………………………………… IV List of Tables ………………………………………………………………….. VII List of Figures …………………………………………………………………. X Abstract ………………………………………………………………………... XI CHAPTER 1 INTRODUCTION ……………………………………... 1 1.1 Overview ……………………………………………….. 1 1.2 Malaysian Engineering Industry Background …………. 2 1.3 Project Management Background in Malaysia ………… 3 1.4 Problem Statement ……………………………………... 4 1.5 Research Rationale …………………………………….. 6 1.6 Research Significance ………………………………….. 6 1.7 Research Objective …………………………………….. 7 1.8 Research Questions …………………………………….. 7 1.9 Organisation of Study ………………..……………….... 8 1.10 Summary ……………………………………………….. 9 CHAPTER 2 LITERATURE REVIEW ……………………………… 10 2.1 Knowledge Management ………………………………. 12

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2.2 Project-based Knowledge ……………………………… 12 2.2.1 Knowledge of Technical Solution ……………. 13 2.2.2 Knowledge of the Organisational Solution …... 14 2.2.3 Knowledge of Business Value ………………... 15 2.3 Project Management Success Criteria …………………. 15 2.3.1 Scope of Work ………………………………... 17 2.3.2 Project Schedule ……………………………… 18 2.3.3 Project Quality ………………………………... 18 2.3.4 Project Budget ………………………………... 19 2.4 Theoretical Framework ………………………………… 19 2.4.1 Integrating Project-based Knowledge with

Project Management Performance ….….……..

19 2.4.2 Integrating Knowledge Management with

Project Management ………………………….

23 2.5 Proposed Project-based Knowledge and Project

Management Success Framework ……………………...

27 2.6 Conceptual Framework …………………………….…... 28 2.7 Hypotheses ………….………………………………….. 29 2.8 Scope of Study …..………….………………………….. 30 CHAPTER 3 RESEARCH METHODOLOGY ……………………… 31 3.1 Overview ………………………………………………. 31 3.2 Research Methodology ………………………………… 31 3.2.1 Research Philosophy of Positivism …………... 33 3.2.2 Deductive Research Approach ……………….. 33 3.2.3 Descriptive Research Approach ……………… 34

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3.2.4 Research Strategy Using Survey ……………... 34 3.2.5 Mono Research Method ………………………. 34 3.2.6 Cross-sectional Research Time Horizons …….. 35 3.2.7 Quantitative Data Collections and Quantitative

Data Analysis …………………………………

35 3.3 Research Design ……………………………………….. 36 3.4 Data Collection Methods ………………………………. 37 3.5 Sampling Procedures …………………………………... 38 3.6 Survey Instrumentation Description …………………… 39 3.7 Data Analysis Techniques ……………………………... 41 CHAPTER 4 RESEARCH RESULTS ……………………………….. 45 4.1 Frequency ………………………………………………. 45 4.2 Tests of Normality ……………………………………... 48 4.3 Bivariate Correlations ………………………………….. 52 4.4 Results for Project Management ……………………….. 66 4.5 Linear Regression Results ……………………………... 66 4.6 Failure Factor Results ………………………………….. 73 CHAPTER 5 DISCUSSION AND CONCLUSION …………………. 76 5.1 Discussion ……………………………………………… 76 5.2 Research Implication …………………………………... 80 5.3 Limitation of Research …………………………………. 81 5.4 Recommendations ……………………………………… 81 5.5 Conclusion ……………………………………………... 82 References ……………………………………………………………………... 83 Appendix A ……………………………………………………………………. 90

VII

LIST OF TABLES Page Table 1: Knowledge of Technical Solution Reliability Statistics 42 Table 2: Knowledge of Organisation Solution Reliability Statistics 43 Table 3: Knowledge of Business Value Reliability Statistics 43 Table 4: Pearson Value Strength 44 Table 5: Frequency Table for Gender 45 Table 6: Frequency Table for Age 46 Table 7: Frequency Table for Years of Experience 46 Table 8: Frequency Table for Job Category 47 Table 9: Frequency Table for Industry Category 47 Table 10: Test of Normality and Descriptive for Knowledge of

Technical Solution, Knowledge of Organisational Solution and Knowledge of Business Value

48

Table 11: Descriptive Statistics for Knowledge of Technical Solution

and Scope of Work in Project Management 52

Table 12: Correlations between Knowledge of Technical Solution and

Scope of Work in Project Management 52


and Quality of the Project 53


Quality of the Project 53


and Controlling Cost of the Project 54


Controlling Cost of the Project 54

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Table 17: Descriptive Statistics for Knowledge of Technical Solution and Project Schedule Control

55


Project Schedule Control 55

Table 19: Descriptive Statistics for Knowledge of Organisational

Solution and Scope of Work in Project Management 56

Table 20: Correlations between Knowledge of Organisational Solution

and Scope of Work in Project Management 56


Solution and Quality of the Project 57


and Quality of the Project 57


Solution and Controlling Cost of the Project 58


and Controlling Cost of the Project 58


Solution and Project Schedule Control 59


and Project Schedule Control 59

Table 27: Descriptive Statistics for Knowledge of Business Value and


Table 28: Correlations between Knowledge of Business Value and







Controlling Cost of Project 62


Controlling Cost of Project 62

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Table 33: Descriptive Statistics for Knowledge of Business Value and Project Schedule Control

63


Project Schedule Control 63

Table 35: Summary of Hypotheses Test 65 Table 36: Respondents Feedback on Ability to Management 66 Table 37: Model Summary of Scope of Work Control as a Dependent

Variable 66

Table 38: ANOVA of Scope of Work Control as a Dependent Variable 67 Table 39: Coefficients of Scope of Work Control as a Dependent

Variable 67

Table 40: Model Summary of Quality Control as a Dependent Variable 68 Table 41: ANOVA of Quality Control as a Dependent Variable 68 Table 42: Coefficients of Quality Control as a Dependent Variable 69 Table 43: Model Summary of Cost Control as a Dependent Variable 69 Table 44: ANOVA of Cost Control as a Dependent Variable 70 Table 45: Coefficients of Cost Control as a Dependent Variable 70 Table 46: Model Summary of Project Schedule Control as a Dependent

Variable 71

Table 47: ANOVA of Project Schedule Control as a Dependent Variable 71 Table 48: Coefficients of Project Schedule Control as a Dependent

Variable 72

Table 49: Failure Factors on Scope of Work Control 73 Table 50: Failure Factors on Controlling the Quality of Project 74 Table 51: Failure Factors on Controlling the Cost of the Project 74 Table 52: Failure Factors on Controlling the Project Schedule 75

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LIST OF FIGURES Page Figure 1: Organisational of Study 8 Figure 2: Theoretical Framework of Project-based Knowledge

Management 20

Figure 3: Knowledge Management Dimensions and Project-based

Knowledge 22

Figure 4: Proposed theoretical framework for project knowledge

sharing contribution to project 23

Figure 5: Knowledge management and project/program management

linked 25

Figure 6: Conceptual Framework 28 Figure 7: Research Onion 32 Figure 8: Histogram for Knowledge of Technical Solution Data 49 Figure 9: Histogram for Knowledge of Organisational Solution Data 50 Figure 10: Histogram for Knowledge of Business Value Data 51 Figure 11: Summary of Hypotheses Test 64

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ABSTRACT This research studies the relationship between knowledge of project-based and project

management success criteria. Hence, the conceptual framework derives from three

previous research models. These combination of theoretical models study on the

contribution of knowledge contribution to project management performance in

engineering project-based organisations. This research is tested on survey data conducted

among the project team members from engineering project-based organisations in

Malaysia. Findings show that knowledge of organisational solution and knowledge of

business value need to be identified and shared among the staffs. Both knowledge of

organisational solution and knowledge of business value are significantly positive

relationship with scope of work control, cost control, and project schedule control.

Besides that, knowledge of technical solution and knowledge of business value statistical

significantly predicted scope of work control, F(3, 36) = 11.774. The limitation of this

research reflects on the statistical results in correlation bivariate test. Most of the

relationships are at the weak and medium strength level.

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CHAPTER 1

INTRODUCTION

1.1 Overview

Project-based organisations provide unique product and service. Project management

represent as a knowledge, skills, techniques and tools to project works to achieve project

necessity among project-based organisations (Lierni, 2004). Most of the project

management literature highlighted that understanding the particular governance

challenges are an important focus for more rigorous research on management of project

(Ahern, Leavy, & Byrne, 2014). Knowledge has been categorised as a critical driving

forces for business success. Therefore, project-based organisations are more focusing on

knowledge intensive and getting more appreciation on knowledge value. Knowledge has

been treated as a kind of tangible resources and many organisations are emphasising on

knowledge management to gain competitiveness and sustainability. Knowledge

management become the basic success requirement for organisations regardless of the

size of business and geographical locations (Wong, 2005).

The practice of knowledge management in project-based organisations usually confront

different challenges. These challenges exist because of the nature of projects that work

on long life cycle and the project teams usually form from different companies with

different knowledge and experience for a short period of time (Hashim, Talib, & Alamen,

2014). Thus, project-based organisations require special knowledge sharing to capture

knowledge from different individuals and convert it to explicit knowledge (Hashim et al.,

2014).

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This paper is focusing on the contribution of knowledge to project management

performance in engineering project-based organisations. A survey is conducted to find

out the impact of knowledge management onto project management. This survey

includes finding factors which causes failure in project management.

1.2 Malaysian Engineering Industry Background

In year 1957, Malaysia gained its independence. Started from independence, the

Malaysian Engineering industry has performed as catalyst in the economic development

of the country (Wong, 2012). The Malaysian engineers improved in term of technology

transfers from foreign engineering firms through partnership in the sixties and seventies

(Wong, 2012). This has allowed the engineers to improve their expertise and skills, so

that world-class standards can be achieved and to commence a multiplicity of giant

projects (Accenture, 2010; IEM, 2001; Judin, 2001). Some remarkable projects were the

Kuala Lumpur International Airport, North-South Highway, Light Rail Transit Systems,

Penang Bridge and Petronas Twin Towers (Hamdan, 1999).

In Malaysia, the engineering industry is observed as one of the key contributors towards

Malaysia economy (Ngai, Drew, Lo, & Skitmore, 2002) about seven to ten percent of the

gross domestic product (GDP) value (Winch, 1995). Additionally, engineering project

usually played a main role in the safety, health and environmental parts of the society

(Bayliss, Cheung, Suen, & Wong, 2004). The Malaysian engineering industry is highly

controlled and protected under the Registration of Engineers Act 1967 (REA). It states

that only qualified Malaysian professional engineers (PEs) are allowed to endorse and

submit construction or project plans to regulatory authorities (Chiam, 2009).

The previous studies on the export performance of Malaysian engineering firm shows

that not many Malaysian engineering firms are providing services to the foreign markets

(Looi, 2003). This could be due to the nature of Malaysia engineering firms which choose

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to operate within their comfort zone (local market) rather than venturing into the

unfamiliar international markets (Wong, 2000; IEM, 2001).

1.3 Project Management Background in Malaysia

Most of the project personnel have learnt both explicit and tacit knowledge through

experiential learning, with majority of the project personnel holding an engineering or

engineering related first degree (Crawford & Gaynor, 1999; PMI, 1999), but very few are

holding the project management degree (Turner & Huemann, 2000). This is supported

by an international cross industry survey, which found that less than 15% of project

personnel currently holding project management certification or registered with

accredited body (Crawford & Gaynor, 1999). Therefore, experiential learning is the only

method of improving competency of the project personnel, and so if project-based

organisations are not emphasising a thoughtful and maintained attempt to support the

experiential learning of their project personnel, so that the outcomes can be achieved

(Turner & Huemann, 2000).

Professional associations have tried to arrange the progression of project management

competence improvement using standards and associated certification programs. Few

standards have been used as guidelines in the project management practice; to supply

guidelines for those involved in managing projects; to define common descriptions of

terms and processes; and act as a foundation for valuation of project management

competence for professional certification or registration. These include (Turner &

Huemann, 2000):

“A Guide to the Project Management Body of Knowledge

ICB: International Project Management Association (IPMA)

Competence Baseline Australian National Competency Standards for Project

Management (AIPM)

PRINCE 2”

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All these standards are focusing on generic project management knowledge, practices and

skills, but are not comprehensive enough to address technical solution, organisation

solution and business values.

1.4 Problem Statement

A project is measured as failure when it has not produced what was expected from the

requirements (Dalcher, 2012; Standing, Guilfoyle, Lin, & Love, 2006). According to

Standish Group’s Chaos Report (2009), there are only 32% of all surveyed projects are

categorised as successful and complied on schedule, on project budget, with the qualities

and proper functionality aspect (Frank, Sadeh, & Ashkenasi, 2011). In other words, a

successful project has to be a project that is being delivered on time with the right quality

and budget which in turn benefits the business case.

When a wrong project is delivered, it can be identified as a failure even it had been

delivered within budget, on time, and pass the standard quality (Storey & Barnett, 2000).

However, if a project has not been delivered according to the client’s requirement, it will

seriously affect the organisational image. Therefore, the business requirement is

importance to start up a project (Storey & Barnett, 2000). If a project cannot be

completed accordingly, it will result in a chain of effect, which includes project's

deadlines, budgets and expectations (Gill, 2008).

Project management skills can be obtained through tacit knowledge, which have been

studied through experiential knowledge in project management based on analysis of

failure and causes (Ioi, Ono, Ishii, & Kato, 2012). This has make practical knowledge

transfer in project management possible (Ioi et al., 2012). Structure, culture, processes

and strategy are the factors of the effectiveness of organisational knowledge transfer

(Rhodes, Hung, Lok, Lien, & Wu, 2008). Besides that, project management team is a

usually a temporary team, who may share their experiences, knowledge and perception

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on works (Yeong & Lim, 2010). Therefore, project manager must create a working

ambient in where knowledge can be identified or created, shared and practiced in project

lifecycle in order to deliver a desired product to client. For these reasons, global

knowledge management is becoming a reality and sustainable value for an organisation

(Yeong & Lim, 2010). It is the only way to make the organisation success and grow in

the future. This indicated that project management personnel have not fully attained and

kept knowledge learned from previous projects to improve success rate on current and

future projects (Yeong & Lim, 2010). However, the previous researches do not have

much emphasis on the relationship between knowledge management and project

management in engineering project management organisations. It is necessary to find out

the importance of knowledge management in order to deliver a successful project and

improve company profit (Lierni, 2004). Besides that, there are very few studies in

knowledge management literature that measure the criteria of a successful project

management, especially in project-based engineering organisations. In fact, there is a

crucial need of forming knowledge management development within organisation in

Malaysia and there is limited research in knowledge management in Malaysian

organisations (Chong, 2006).

This research project will show the contribution of knowledge management to project

management in engineering project-based organisations. This research will be looking at

three types of project knowledge and their influence on project management in a project

based organisation. Scope of work, quality work, project budget, and project schedule

will be studied as the measurement of a successful project management. According to

Todorović, Petrović, Mihić, Obradović, & Bushuyev (2015), knowledge management in

project-based organisations is an insufficiently studied area in project management. In

the past, the researches focused on individual case, specific project types and case studies

on industries (Todorović et al., 2015). Over the last couple of years, researchers started

to study the influence of knowledge management on project performance (Todorović et

al., 2015).

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1.5 Research Rationale

In fact, knowledge workers teams can contribute accumulated knowledge to project team

(Zhao, Zuo, & Deng, 2015). Project management knowledge transfer bring a position

effect on project outcome, in order to improve project execution process and recover

project efficiency and service quality (Zhao et al., 2015). However, project management

knowledge transfer is not always positive (Newell & Edelman, 2008). Project-based

organisations find difficult to store knowledge learned and document it (Newell &

Edelman, 2008). The problems existed on project management knowledge transfer give

negative feedback on the organisation development and project management capabilities,

affecting organisation performance in the long term (Zhao et al., 2015). Therefore,

method of project knowledge management challenges to project-based organisations,

managing knowledge and transfer on project management is a complex challenge need to

be studied.

1.6 Research Significance

One of the criteria of a successful organisation is that it is able to turn ideas into action

and recognise effective knowledge transfer as essential to their competitive advantage

(Profession®, 2015). Knowledge transfer is implanted in the culture of the effective

organisations because they are knowingly more likely to appreciate the knowledge

transfer progressions that are in place (Profession®, 2015).

The unpredictable condition of projects create major challenges for project leaders and

project-based organisations (Ajmal, 2009). The findings of this research will provide the

up to-date information towards the current situations on the Malaysian engineering

industry. Perception of engineers or engineering stakeholders on knowledge

management will be examined in future research.

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Besides that, this research may implicate for project-based organisation in order to handle

knowledge management. There are three knowledge fields to be studied, the result of

research can be the focus of the project-based organisation in order to implement

knowledge management within the organisation. Based on the research report,

organisation is able to focus the most important direction of knowledge to give training to

their staffs. Besides that, the execution of knowledge management can be effectively

improved.

1.7 Research Objective (RO)

In link with the problem statement this study enclosed the following objectives:

a) To verify the contribution of knowledge management towards project management.

b) To verity the relationship of project-based knowledge categories to success project

management criteria.

c) To identify factors of implementation knowledge management in success project.

d) To identify difficulties of execution knowledge management in engineering

companies.

1.8 Research Questions (RQ)

This research will be examined the following questions:

a) What are the contribution of knowledge management towards project management?

b) How to relate project-based knowledge categories to success project management

criteria?

c) What are the factors of implementation knowledge management in success project?

d) What are the difficulties of execution knowledge management in engineering

companies?

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1.9 Organisation of Study

Figure 1: Organisational of Study

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1.10 Summary

Four research questions will be explored in this study. These research questions can be

employed to explain on research objectives of the research. There are three project-based

knowledge to be studied in order to relate to project management success criteria.

Conclusively, this conceptual framework will be able to contribute to the project-based

organisations. The reason of choosing these three field of knowledge will be further

explained in the chapter two.

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Chapter 2

LITERATURE REVIEW

Project failure create a damaging image to the project-based organisations (Sage, Dainty,

& Brookes, 2014). There are three reasons that lead to failures in engineering project,

such as the instability of the market condition, the complication of organisation, and the

failure in controlling and management (Geppa, Hellmuth, Schaffler, & Vollmar, 2014).

Lee & Choi (2003), Quigley, Locke, & Bartol (2007), Kotnour (2000), and Barber &

Warn (2005). These confirmed that there are positive influence of knowledge

management on project performance.

Knowledge management has been acknowledged as a key factor for project success

(Sokhanvar, Matthews, & Yarlagadda, 2014). The high mobility among project team

members caused several issues, such as reparative activities, leaking of project

knowledge and double works, become a major challenges in project-based organisations

(Sokhanvar et al., 2014). Most of the researches identified the challenges of knowledge

management in project environment are as below:

“The lack of routines and other appropriate learning mechanisms, as well as the

availability of the previously learned lessons and reports from the previous

projects.

Documenting project operations, i.e. recording their organisational processes,

rarely fail to fully reflect the course of procedures and activities, which is why

their purposefulness is doubtful.

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The lack of efficient and effective forecasts, insufficient communication and

exchange of information, inadequate use of the previous experience and lessons

learned.

The uniqueness of projects and their long life cycle; therefore, a long time interval

passes before lessons are retrieved, while projects' temporary nature requires new

team meetings for each project.

Action-and-task orientation of project-intensive organisational structure (i.e.

temporary organisation), where project team members are not geared for learning.

Individuals become more able and experienced; nevertheless, there is often no

mechanism or motivation for that knowledge to be shared within the company.

A contradiction between short-term goals of projects and long-term goals of

organisational learning, where knowledge management depends on the degree of

projectisation of the company, i.e. on the level of a firm's project maturity”

(Todorović et al., 2015).

The literature review consists of two portions, first part covered the background of

theoretical framework in project-based knowledge and project management success

criteria. Secondly, discussion on the factors and difficulties of implementation of

knowledge management to the project management success. The background

information on project-based knowledge and project management criteria assists the

understanding of the correlation of dependent variables and independent variables of the

research. Background information on literature review provided primary input to start up

a conceptual framework and the breakdown of project-based knowledge that may

influence project management success. Besides that, the project management success

analysis process contains the process of gathering necessary information to evaluate

project performance, this identified that project management success has to be connected

with knowledge management in project-based organisations in order to increase the

knowledge data base. In summary, the preliminary study is used to gain a useful

understanding of both knowledge management and project management. Based on the

insight gained from literature review helped in casting the conceptual framework. The

ultimate goal of the study is to justify the correlation of dependent variables and

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independent variables on the conceptual framework and provide solution or proposed

solution to research questions mentioned in Chapter 1.

2.1 Knowledge Management

Knowledge management research started in 1970s and the impact of the research

contributed to method of knowledge producing, knowledge used within organisations

(Lierni, 2004). The development of information technology assisted in technological

base for managing knowledge, especially in United States (Lierni, 2004). In the mid-

1990s, the internet development improved knowledge management, few researchers have

contributed to the revolution of knowledge management (Lierni, 2004). Nowadays,

knowledge management is directed to a kind of business in major international

professional organisations. They have applied knowledge management to their areas of

expertise (Lierni, 2004). At the same time, knowledge management has been applied to

project management. Some literature review explores mentioned on the awareness and

accessibility of knowledge in project risk and it has extended to organisational risk

(Lierni, 2004). Knowledge management is able to provide productive information apply,

intelligence enhancement, activity improvement, strategic planning, intellectual capital

storage, best practice gathering, flexibility acquisition, success probability enhancement

and productive collaboration (Kanapeckiene, Kaklauskas, Zavadskas, & Seniut, 2010).

2.2 Project-based Knowledge

In fact, knowledge is an asset to an organisation as competitive advantages on the linkage

of core competence and knowledge (Yeong & Lim, 2010). Improper way of managing

knowledge during project lifecycle will result in valuable intellectual capital to be

devalued and lost efficiency in work. Knowledge can be categorised into two types, tacit

knowledge, which is personal knowledge and difficult to be expressed in words and

explicit knowledge, which is tangible expressed in words and able to be stored in term of

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documents (Seufert, Back, & Krogh, 2003). Seufert et al., (2003) expressed knowledge

as a continuous flow process such as localising and identifying; sharing and transferring;

creating and applying. In another word, knowledge management is a process to enable

new knowledge creation, while improving the innovation. Thompson (2003) argued that

knowledge management as a contribution to a cost saving productivity environment.

Broad range of explicit knowledge will created, stored, accessed, used and updated

during the undergoing of a project (Reich, Gemino, & Sauer, 2012). This research

emphasizes on three type of knowledge, the technical solution knowledge (developed by

technical team), organisational knowledge (developed by management) and business

value knowledge (developed by business team). Reich et al. (2012) stated that

knowledge management produces identified team of knowledge within a project, which

knowledge is important to complete project goals successfully. Even though, some of the

knowledge keep on tacit, but it is still necessary to convert those knowledge to explicit,

so that it can be evaluated, monitored, share and modified, and used (Reich et al., 2012).

Lessons learned (knowledge) from previous project can benefit to far-reaching changes

on strategic focus in an organisation. The knowledge and expertise established within

project teams positively impacts to organisational success in creating valuable knowledge

in project development (Todorović et al., 2015). Knowledge becomes a solution for

problems and technology that might inspirit the project results and technical design

knowledge relating to a project implementation (Todorović et al., 2015).

Each type of project-based knowledge is defined below with backup literature.

2.2.1 Knowledge of Technical Solution

Technology has improved rapidly to develop technical roles at the project industry. The

idea of project technical improvement is to provide an acceptable technical solution to

achieve corporate architectural standards (Reich et al., 2012). Project technical team

must able to apply technology into project and integrate technology to improve the

design. There are dynamical revolution of technical knowledge, old technology can be

emerged with latest technology within the time frame if a project. Reich et al. (2012)

defines that technical solution knowledge as a “dynamic, shared understanding of the

14

architecture and infrastructure of the technical solution within the context of any wider

architectural standards or infrastructure standards and constraints” (p. 667).

Technical knowledge focuses on the product and services. According to Lehtimaki,

Simula, & Salo, (2009) technical knowledge can be categorised to core knowledge and

project specific knowledge. Core knowledge is used to improve project teams, but

project knowledge is useful for one project and hardly to be used again (Lehtimaki et al.,

2009). Project-based organisation need to show that it has competency in technical

knowledge and justify that this knowledge is beneficial to the proposed project

(Lehtimaki et al., 2009). Besides that, project specific knowledge needs to be highlighted

during the diagnosis of customer problems (Lehtimaki et al., 2009). However, core

knowledge and project specific knowledge are both important factors in building trust.

Each project is distinctive on the technical, trust-generating and people involved, thus, it

must be tailored to each individual project (Lehtimaki et al., 2009). Feo (2003) identified

that project teams with higher technical knowledge, skills and abilities execute better

tasks than those that do not. Besides that, Feo (2003) also stated that bigger project team

will contribute larger technical knowledge, which can benefit to projects.

However, Langer et al argue that non-technical or tacit knowledge (soft skills)

significantly improve both cost control and client’s satisfaction. The impact of soft skills

is greater than knowledge of technical solution. Additionally, soft skills is able to

improve coordination among the project team and also with clients. Soft skills has been

proven to be helpful for project team members to develop and implement better project

management practices.

2.2.2 Knowledge of the Organisational Solution

According to project literature, welfares are only protected if a new system is

collaborated by business practice and organisational alteration (Reich et al., 2012).

Morton (1991) states that the combination models express the gratitude of the strategy,

structure, process and people need to be collaborated to core technology systems to attain

high performance. Knowledge of the organisational solution refers to the organisational

15

changes, such as structure changes, processes changes, incentives changes, skills changes

and culture changes. These changes required to bring in IT additive and realise value

(Reich et al., 2012). Reich et al. (2012) defines knowledge of the organisational solution

as “the dynamic shared understanding of the changes that need to be made in the

organisation in order to utilise the technical solution to enable the attainment of the

desired business value” (p. 667).

2.2.3 Knowledge of Business Value

Understanding on desired business value becomes a main success factors for IT project

(Reich et al., 2012). Some literature reviewed that IT projects have justified the

important of business value (Reich et al., 2012). Reich et al. (2012) emphases that

chances may commence throughout a project through the business implication of the

technology learning. Reich et al. (2012) defines knowledge of desired business value as a

“dynamic shared understanding of the business objectives that the project is expected to

deliver” (p. 666). Therefore, project team must progressively review on the factor of

producing business value.

2.3 Project Management Success Criteria

In fact, project management practices are getting more and more important, some project

management standards and methodologies have been established by academic and

industrial research to improve project-based organisations (Sokhanvar et al., 2014). The

Institute’s Project Management Body of Knowledge guide (PMBOK) clearly states that

project as a short-term body undertaken to produce an exclusive product or service

(Yeong & Lim, 2010). Additionally, project management is explained as “the application

of knowledge, skills, tools and techniques to project activities to meet the project

requirement” (Yeong & Lim, 2010, p. 9).

16

On the other hand, PRINCES2 guide defines project as “a temporary organisation that is

created for the purpose of delivering one or more business products according to an

agreed business case” (Yeong & Lim, 2010). According to the PRINCE2 guide, project

management is defined as “the planning delegating, monitoring and control of all aspects

of the project, and the motivation of those involved, to achieve the project objectives

within the expected performance targets for time, cost, quality, scope, benefits and risks”

(Yeong & Lim, 2010, p. 9).

There are another definitions of project and project management from the Project

Management Association of Japan (PMAJ). According to PMAJ’s Project & Program

Management guide (P2M), which is exceedingly considered by the project management

professional in Japan, project is defined as a “value creation undertaking based on

specific, which is completed in a given or agreed time frame and under constraints,

including resources and external circumstances” (Yeong & Lim, 2010). The project

management refers to “the professional capability to deliver, with due diligence, a project

product that fulfils a given mission, by organising a dedicated project team, effectively

combining the most appropriate technical and managerial methods and techniques and

devising the most efficient and effective work breakdown and implementation routes”

(Yeong & Lim, 2010).

Based on the PMBOK, the improvement in project management can have a major effect

on project success (PMI, 2008). The improvement can be justified from the practising of

suitable knowledge, process, skills, tools, and techniques (PMI, 2008). The goal of

project management is to make sure the project to be accomplished to fulfil the

requirement of scope specified by stakeholders, within budget, complete a quality

product or service on time (Yeong & Lim, 2010).

In fact, project success can be proven that the project accomplished with the right time,

cost and quality (Yeong & Lim, 2010). However, this justification on project success is

simplistic and even dangerous (Turner, 2009). Turner (2009) argues that a project was

completed on budget and within schedule but after few years it can be judged to be a

disappointment. Turner (2009) mentioned that project stakeholder, like sponsors, users

17

and project manager, have different judgments on project success. It is better to get a

balance on project success criteria among project stakeholders (Turner, 2009). There is

very difficult to judge whether a project management is successful, a project delivered

within budget, construct based on performance requirement and complete on time, but it

may not be able to judge whether project was executed properly (Kerzner, 2009).

Turner (2009) lists nine specifications for measuring project success:

“The project increases the shareholder value of the parent organisation.

The project generates a profit.

The project provides the desired performance improvement.

The new asset works as expected.

The new asset produces a product or provides a service that consumers want to buy.

The new asset is easy to operate.

The project team has a satisfactory experience and the project met their needs.

The contractors made a profit” (p. 67).

2.3.1 Scope of Work

The scope of work of the project is the benchmark of the deliverable product or services.

During the commencement of project, the project team refines the scope of work and

improve a preliminary schedule and conceptual budget. The scope of work is

documented as design parameter that determine the deliverables of the project. Even a

clear project scope document need to change during the project (Clements, Drysdale,

Francis, Harrison, Rino, Robinson, & Snyder, 2012). Scope of work reflects to the work

need to be accomplished on the project, any alteration in expectations which is not

captured creates chances for confusion. The most commonly happens is the incremental

expansion in the project scope. This expansion of work affect the success of a project

because additional of scope require additional resources. However, amendment of scope

of work is a common occurrence (Clements et al., 2012) and this adjustment will impact

to project budget and schedule. The ability of a project team leader to identify possibility

of amendment will improve the quality of scope documents.

18

2.3.2 Project Schedule

Project schedule is the project duration from start to completion of the project. Schedule

can be an important issue for many clients, it can be primary consideration issue,

especially for production clients. Project schedule overruns give impact to a vicious

circle problem (Bjarnason & Hochdorfer, 2007). The vicious circle means project team

members have to work on too many projects at the same time. Consequently, it is

difficult to focus on every single project. Thus, some of project start to slip and it takes

extra time and effort to cope up with these schedule and subsequently result in less

efficiency in work. Poor project schedule will result in low quality of work and damage

the outcome of project and image of overall organisation (Bjarnason & Hochdorfer,

2007). In order to well manage a project, project manager must know how to expedite

the schedule to compensate for unanticipated event that cause delay.

2.3.3 Project Quality

The quality refers to the end product or deliverables services that serve the goal of the

project (Clements et al., 2012). The project management success is measured from

project execution approach that delivered the expected deliverables projects based on

specified quality. However, the concept of quality is closely depended on customer

satisfaction. Customer satisfaction is justified based on the comparison between the

customer’s pre-order perceptions and post-order expectations (Eriksson & Westerberg).

Project team members is responsible for executing a project quality that documented in

quality expectations and assures that the specification and expectations are met. A proper

documenting on project specifications and expectations is important to a good quality

plan (Clements et al., 2012). These are necessary to integrate into project execution plan.

It is as same as project schedule and budget, changes in quality specifications may occur

across the project life cycle. Cost and schedule is the impact of changes of quality,

because of the limited period of a project and increases the cost of the project. Therefore,

time, appropriate skills, materials, and project planning is measurement to project success

(Clements et al., 2012). Project-based organisation may use the process improvement

tools to identify and improve the baseline processes used on the projects. The PMBOK

19

has identified that process improvement tools is helpful to monitor cost and schedule

improvement opportunities.

2.3.4 Project Budget

The project success often includes commissioning the project within budget (Clements et

al., 2012). Controlling the project budget is the critical project management skill. Client

would like to complete the project with the shortest period, but this will impact on the

budget of the project. The development of cost controlling is necessary to monitoring the

budget and company cash flow (Clements et al., 2012). According to Clements et al.

(2012), the project budget is associated to the number of information known by the

project team. At beginning stage, the information needed to work out the costing is

limited. To solve this issue, the project team need to develop different level of cost

estimation. This estimation required the expert knowledge or past experience (Clements

et al., 2012). Traditionally, well controlling on project cost can be seen as a success in

project management (Eriksson & Westerberg).

2.4 Theoretical Framework

Section 2.1, 2.2 and 2.3 explained the knowledge management and project management.

This section discusses the theoretical framework of knowledge management with project

management to make project success.

2.4.1 Integrating Project-based Knowledge with Project Management

Performance

Figure 2 explains the theoretical framework that knowledge management involves of

knowledge stock, enabling environment and knowledge practices (Reich, Gemino, &

Sauer, 2014). These three knowledge produce project-based knowledge, which pertain to

knowledge of the technical solution, knowledge of the organisational solution and

20

knowledge of expected business value. Both knowledge management and project-based

knowledge give impact to level of knowledge alignment in the project. Knowledge

alignment refers to the similarity of understanding of the teams. Conclusively,

knowledge management, project-based knowledge and knowledge alignment will

influence both project management performance and project performance (Reich et al.,

2014).

Figure 2: Theoretical Framework of Project-based Knowledge Management

Note. Sourced from Reich, B. H., Gemino, A., & Sauer, C. (2014). How knowledge

managment impacts performance in project: An empirical study. International

Journal of Project Management, 32, 590-602.

This framework showed that the goal of knowledge management is two-fold (Reich et al.,

2014). The first goal is to achieve the project’s business value through technological and

organisational solutions. The second goal is to achieve a level of shared understanding

across the professional team. The organisational team in-charge on business change and

the business sponsors with knowledge must achieve for the business.

21

The first goal is to ensure the proposed solution for the project should obtain the business

successive. The second goal is to ensure sufficient sharing and understanding among the

team during executing of the project. In case of unanticipated changes, other team

members can recognise the impacts and solutions. According to Reich et al. (2014), the

purpose of knowledge management does not create equality knowledge among project

team members, but to equip them to understand their expertise and alert to the

consequences on their decision make to give impact to others.

Figure 3 refers to the two principal basics of knowledge management and project-based

knowledge. There are three dimensions of knowledge management contains of

knowledge stock, enabling environment and knowledge practices (Reich et al., 2012).

This model represents that knowledge is produced from knowledge practices, using

knowledge stock as contribution and working within an enabling environment. Thus,

knowledge management impacts to project-based knowledge and aligned project-based

knowledge (Reich et al., 2012). Additionally, project-based knowledge created from

three key type, such as organisational solution, technical solution and desired business

value.

22

Figure 3: Knowledge Management Dimensions and Project-based Knowledge

Note. Sourced from Reich, B. H., Gemino, A., & Sauer, C. (2012). Knowledge

management and project-based knowledge in it projects: A model and

preliminary empirical results. International Journal of Project Management, 30,

663 - 674.

Additionally, the role of effective knowledge management is proven to produce

innovation, reduce project time and improve quality and customer satisfaction

(Kanapeckiene et al., 2010). Other researchers mentioned that knowledge management is

able to create value for organisation’s intangible assets and both internal and external

knowledge, thus useful to the organisations (Kanapeckiene et al., 2010). In fact, projects

knowledge management can enhance communications within teams through providing

more informative sharing on best practice documents, project management and system

engineering methodologies, lesson learned, and review rationales of strategic decisions

making (Kanapeckiene et al., 2010).

23

2.4.2 Integrating Knowledge Management with Project Management

Ismail, Nor, & Marjani (2009) studied the method of individual knowledge sharing in

project environment. This research theoretical framework (figure 4) shows that

delivering appropriate motivator and eliminating applicable inhibitors to sharing

knowledge and experience would contribute to the more effective and efficient in project

knowledge sharing and increase to the project success rate (Ismail et al., 2009). This

model was referred to Nonaka’s Knowledge Conversion Model (1998) and emphasises

on the socialisation of tacit knowledge. Inclusively, Ismail et al. (2009) explained that

the essential for project success is based on the process of tacit and explicit knowledge

sharing.

Figure 4: Proposed theoretical framework for project knowledge sharing contribution to

project

24

Note. Sourced from Ismail, W., Nor, K., & Marjani, T. (2009). The role of knowledge

sharing practice in enhancing project success. Institute of Interdisciplinary

Business Research.

Cope III, Cope, & Hotard (2006) also conclude that knowledge management practices

that to improve project management. If both tacit and explicit knowledge from previous

projects could be identified and shared on the new project, it would beneficial to the

organisation (Cope III et al., 2006).

Project managers agreed that the use of knowledge management practices is positively

impacted on the management of project (Lierni & Ribiere, 2008). Shared Repository pf

Project Artifacts, Lessons Learned and Best Practices Repositories, and Document and

Content Management Systems are the most adoptable knowledge management practices

to helping project manager (Lierni & Ribiere, 2008). Lierni & Ribiere (2008) suggest

that explicit knowledge sources comes first, but project managers gain knowledge from

knowledge sharing and codifying tacit knowledge from former projects.

Another framework, proposed by Gudi & Becerra-Fernandex (2006), this framework

emphasise that the motivation to diminish risk and prevent failure through the focusing

on the dynamic feature of project management using knowledge management as shown

in figure 5 (Gudi & Becerra-Fernandez, 2006).

25

Figure 5: Knowledge management and project/program management linked

Note. Sourced from Gudi, A., & Becerra-Fernandez, I. (2006). Role of knowledge

management in project management if complex systems organizations. NASA

Knowledge Management and Successful Mission Operations Conference 2006.

Houston, TX.

The understanding of natural risk of the systems will minimise or eliminate risk of failure

and improve the opportunity of project success (Gudi & Becerra-Fernandez, 2006).

When project develops more complex, organisation has to understand the inter-related

activities of the project, in order to recognise knowledge management strategies. These

strategies are able to reduce project failure rate and increase project success rate (Gudi &

26

Becerra-Fernandez, 2006). Knowledge management mechanisms, process and

technologies are suitable for project management requirement. In fact, political and

economic factors (external), innovation and complexity factors (internal) will influence to

project risk (Yeong & Lim, 2010). Same as previous literature, project success refers to

scheduling, budget and functionality.

Finally, Levin (2010) states that effective knowledge management execution is the main

success of project management in project-based organisations. Knowledge management

has to be combined with project management for rapid feedback to collect data in order

to provide solution to the problems and share information effectively and efficiently

(Levin, 2010). The necessary to combine knowledge data base to project management so

the project team can integrate individual contributions to complete the project’s goal and

bring into cooperation to achieve organisation’s strategic objectives (Levin, 2010).

There are nine guidelines for organisation to have successful execution and integration of

knowledge management with project management:

“Define knowledge management so that everyone in the organisation can

understand it

Make knowledge management to be a work package in the work breakdown

structure of every project

Establish a point of contact for knowledge management on each program and

project working with the Enterprise Project Management Office

Use a Responsibility Accountability Matrix (RAM) to define roles,

responsibilities, and accountabilities for knowledge management

Communicate the importance of knowledge management to all stakeholders

throughout the organisation

Provide knowledge management orientation and training to all stakeholders

Establish a practical knowledge management reward and recognition system

Track the usefulness of knowledge management by using metrics

Organisation should focus on continuous improvement” (Levin, 2010).

27

2.5 Proposed Project-based Knowledge and Project Management

Success Framework

Based on the literature study, the proposed framework has been generated from the

merging of three models of knowledge management and project management as below:

Model of knowledge management dimensions and project based knowledge

(Reich et al., 2012)

Model of project-based knowledge management (Reich et al., 2014)

Model project knowledge sharing contribution to project (Ismail et al., 2009).

As discussed in section 2.4.1, the previous research model represents that knowledge is

produced from knowledge practices, using knowledge stock as contribution and working

within an enabling environment. Thus, knowledge management will affect project-based

knowledge and aligned project-based knowledge (Reich et al., 2012). There are three

type of key project-based knowledge creation, which includes organisational solution,

technical solution and desired business value.

Since, theoretical framework of project-based knowledge management (Reich et al.,

2014) represents that knowledge management, project-based knowledge and knowledge

alignment will influence both project management performance and project performance.

However, Ismail et al. (2009) explained that the essential for project success is based on

the process of tacit and explicit knowledge sharing. The project management success is

measure from scope of work, project cost, completion within schedule and quality of

project (Ismail et al., 2009).

28

2.6 Conceptual Framework

Three project based knowledge influence on project management success criteria will be

studied in this research. Project-based knowledge can have significant impact on the

project management success. Therefore, the combination of theoretical models study the

contribution of knowledge contribution to project management performance in

engineering project-based organisations as shown in figure 6. Finally, the relationship

between knowledge can be determined. The framework below defined the research

objectives and research questions as stated in chapter 1.7 and 1.8 respectively. The

independent Variables (IVs) of the Project-based Knowledge we turned into hypotheses.

The researcher used statistical tests to analyse the potential relationship between the IVs

and DVs (Figure 6).

Figure 6: Conceptual Framework

The next chapter, chapter 3 presents the methodology of the research used in analytic the

relationship and correlation of project-based knowledge and project management success

criteria.

29

2.7 Hypotheses

H1a) There is a significant relationship between knowledge of technical solution and

scope of work in project management.

H1b) There is a significant relationship between knowledge of technical solution and

quality of the project.

H1c) There is a significant relationship between knowledge of technical solution and

controlling cost of project.

H1d) There is a significant relationship between knowledge of technical solution and

project schedule control.

H2a) There is a significant relationship between knowledge of organisational solution

and scope of work in project management.

H2b) There is a significant relationship between knowledge of organisational solution

and quality of the project.

H2c) There is a significant relationship between knowledge of organisational solution

and controlling cost of project.

H2d) There is a significant relationship between knowledge of organisational solution

and project schedule control.

H3a) There is a significant relationship between knowledge of business value and scope

of work in project management.

30

H3b) There is a significant relationship between knowledge of business value and quality

of the project.

H3c) There is a significant relationship between knowledge of business value and


H3d) There is a significant relationship between knowledge of business value and project

schedule control.

2.8 Scope of Study

Project-based organisations have gain more interest in emerging organisational structure

to intellectual resource to develop organisational culture and innovation (Ajmal, 2009).

By improving organisational economy, project organisations reinforce their knowledge

resources in an efficient method (Ajmal, 2009). Knowledge management in the

environment of a project-based business planning is increasing in sustaining competitive

advantage. According to (Love, Fong, & Irani, 2005), knowledge management is an

alternative task among project-based organisations because these organisations require

organisational mechanisms for knowledge transfer from one project to others project.

This research focuses on exploring the project-based knowledge correlated to project

management success among project-based organisations. The goal of this research is to

develop an understanding of impact of knowledge management to the project

management. This can be used as a measuring tool on implement the project knowledge

among project-based organisations.

31

CHAPTER 3

RESEARCH METHODOLOGY

3.1 Overview

This chapter consists of the research methodology and questionnaire development and

design which describe more on survey research and questionnaire design and content

issues. Survey questionnaire is distributed to engineering project-based managers and

engineers, to study the contribution of project-based knowledge on project management

performance. This descriptive and inferential statistical analyses were conducted using

the 0.05 confidence level to determine statistical significance. As stated in chapter 1, this

research is to study the contribution of knowledge management to project management

performance in engineering project-based organisations. The research topic covers

across the project-based knowledge.

3.2 Research Methodology

Research methodology based on research onion (Saunders & Tosey, 2013), it describes

the stages that must be included when starting a research strategy (Kura, 2012). The

Research Onion provides a progressive method for research methodology design. This

research focuses on obtaining data from engineering project-based organisations. Survey

questionnaire is used to collect data of the research. Selection of techniques used to

obtain data and analyse these data to represent the overall research design. Research

32

onion directs researcher’s understandings from outer layers that give the context and

boundaries within the data collection techniques and analysis method to be taken.

Figure 7: Research Onion

Note. Sourced from Saunders, M., Lewis, P., & Thornhill, A. (2009). Research methods

for business students (5th ed.). England: Pearson Education Limited.

This research studies the contribution of knowledge management on project-based

performance. It covers relationship between project-based knowledge and the success of

project management within the engineering project-based organisations. A variety of

researches have been conducted in the field of project management (Ajmal, 2009). This

research makes use of a quantitative approach to conduct an empirical part, it is dealing

with cause and effect thinking, reduction to specific variables, questions and hypotheses,

measuring and testing (Ajmal, 2009). Quantitative research is an appropriate study to be

33

conducted, it is suitable to identify the signification relationship between independent

variables and dependent variables (Ajmal, 2009).

3.2.1 Research Philosophy of Positivism

Research philosophy explains how data will be collected, analysed and applied. It refers

to believe of concerning of the nature of the reality being studied (Saunders, Lewis, &

Thornhill, 2009). Philosophy is defined as a kind of knowledge being studied in the

research (Essays, 2013). Understanding of research philosophy being employed, it can

aid to describe the assumptions inherent in the research process and how this suits the

methodology being engaged (Essays, 2013). Positivism recognized that reality is stable

on the phenomena being studied (Kura, 2012). According to Hinkelmann and Wistshel,

positivist believes in the possibility to observe and describe reality from an objective

viewpoint. It observe the world in some neutral and goal, derive theories, and discover

universal laws. Positivism generates hypotheses which can be tested and explanted

against existing laws and theories.

3.2.2 Deductive Research Approach

There are two types of research approaches, the deductive approach and inductive

approach (Saunders et al., 2009). The deductive approach states the hypotheses upon a

pre-existing theory, then derives the research approach to test it (Saunders et al., 2009).

Deductive approach is the best fit to contexts the research studying on the observed

phenomena suit with expectation based on previous studies (Essays, 2013). Deductive

approach suits to positivist approach, which allows the derivation of hypotheses and

statistical analysis of expected outcomes to an acceptable level of probability (Essays,

2013). Deductive approach can be used for qualitative research techniques, therefore the

expectations on previous studies would be formulated differently than the hypotheses

testing (Saunders et al., 2009). This approach uses general theory to establish knowledge

gain from the research process and then tested against it (Kothari, 2009).

34

3.2.3 Descriptive Research Approach

Descriptive research approach refers to the method of research question, design and data

analysis that to be used to a given topic. Descriptive researches focus on “what is” in

order to find out the answer of the research questions and usually to be used to collect

descriptive data (Spector, Merrill, Elen, & Bishop, 2014). Descriptive research does not

restrict to quantitative research but it also applies to qualitative research (Borg et al.,

1993). Descriptive studies analysis measure mean, median, mode, deviance from the

mean, variation, percentage, and correlation between variables (Spector et al., 2014).

Survey research usually take into consideration on the type of measuring and goes

beyond the descriptive statistics to get conclusions (Spector et al., 2014).

3.2.4 Research Strategy Using Survey

The research strategy is the method of researcher to collect data and conclude the pattern

of the study, the strategy of study consists of experimental research, action research, case

study research, interviews, surveys or a systematic literature review (Saunders et al.,

2009). Surveys methods tend to be used in quantitative research, sampling size need to be

representative proportion to the population (Saunders et al., 2009).

3.2.5 Mono Research Method

There are three choices of research method, such as mono-method, mix-method and

multi-method (Liu, 2013). Research can be qualitative, quantitative or a combination of

both. As the names of choices, mono-method is using single research approach for the

study (Essays, 2013). Mixed-method consists of two or more methods of research

(Essays, 2013). For mono method quantitative research, data were collected through

survey questionnaire, the quantitative research is more suitable to be used to examine the

relationship between variables (Liu, 2013).

35

3.2.6 Cross-sectional Research Time Horizons

The Time Horizon is the time frame for research to be completed (Essays, 2013), it can

be categorized into cross-sectional studies and longitudinal studies. The cross sectional

time horizon is an established time frame, which the data must be taken (Essays, 2013).

This states that data are collected within a period of time. Cross-sectional research

applies to the study that concern the research phenomenon at a specific time (Sekaran &

Bougie, 2009). Saunders et al. (2009) specified that cross-sectional studies usually use

for survey strategy, it can be used to describe the incidence of a phenomenon, like the IT

skills possessed by managers in an organisation at a specific time or how factors are

related in different organisations.

3.2.7 Quantitative Data Collections and Quantitative Data Analysis

Quantitative and qualitative studies are used generally in business and social research.

Qualitative is used mainly for interview as a data collection technique and categorising

data procedure as a data analysis method. In contrast, quantitative is generally using

questionnaire as a data collection method and statistical or graph analysis to study data

(Saunders et al., 2009).

For social science research, questionnaires is the greatest used survey strategy (Sekaran

& Bougie, 2009). In fact, questionnaires data collection technique is the most common

technique and efficient way of collecting data from a large designated sample (Saunders

et al., 2009). Before using questionnaire survey, researcher need to ensure that survey

will collect the precise data to answer research questions in order to achieve research

objectives. However, questionnaires are not recommended to be used for a research

involve large numbers of open-ended questions (Saunders et al., 2009). According to

Saunders et al. (2009), survey questionnaire work best with standardised questions that

can be easily understand and same interpretation by all respondents. Even though,

questionnaires can be used as a data collection method, it is better to connect them with

other workable methods as a multiple-methods research design (Essays, 2013).

36

There are variety of factors will influence on the choice of questionnaire (Saunders et al.,

2009, p.363):

“Characteristics of the respondents from whom you wish to collect data.

Importance of respondents’ answer not being contaminated or distorted.

Importance of reaching a particular person as respondent.

Size of sample you require for your analysis, taking into account the likely

response rate.

Types of question you need to ask to collect your data.

Number of questions you need to ask to collect your data”.

Quantitative data is a raw of numbers, need to be processed to make them useful to

become information to researcher. Charts, graphs and statistics help to describe and

examine relationships and trends within collected data (Saunders & Tosey, 2013). In

fact, social science and business management research involve some numerical data to be

quantified in order to answer research questions and meet research objectives (Saunders

et al., 2009). Quantitative data can be categorised into two group, categorical and

numerical. Categorical data refer to data cannot be measured numerically but can be

group into categories based on characteristics (Saunders et al., 2009). However,

numerical data can be measured or countable, this means that numerical data are more

accurate than categorical as it can be analysed using statistics (Saunders et al., 2009).

3.3 Research Design

The purpose of this study is to determine if there is a significant relationship between

project-based knowledge and the project management success. The outcome of the

research will give better understanding of which (if any) project-based knowledge are

able to improve project management success. If these knowledge management is

applicable to improve project management, an expansion of knowledge management in

project-based organisations will be apply accordingly.

37

The research employed a descriptive and survey questionnaire evaluation design.

Researcher liaises with Project Management Institute (PMI) Malaysia for the respondents

name list. PMI is a worldwide recognised non-profit project management professional

association. Therefore, the results should mainly allow the researcher to conduct a

findings on the research objectives (Lierni, 2004). This study focuses on the project-

based organisations in Malaysia. Targeted companies must be doing engineering project.

The list of targeted samples is provided by Project Management Institution, Malaysia.

The respondents of the survey form must be a project manager of engineering project-

based company. To achieve the objective of this research, the following four research

questions were examined:

a) What are the contribution of knowledge management towards project management?

b) How to relate project-based knowledge categories to success project management

criteria?

c) What are the factors of implementation knowledge management in success project?

d) What are the difficulties of execution knowledge management in engineering

companies?

3.4 Data Collection Methods

This research data were collected through survey questionnaire. The survey design a

single-stage and cross-sectional and data collected at one point in time. Surveys are

always the most appropriate strategy apply to research, which allow questions to directly

aim specific topics (Lierni, 2004). According to Lierni (2004), the speed of collection as

well as economy method are the benefits of choosing survey as a data collection. It also

protect respondents as the data to be collected anonymously. The survey was gone

through both web-enabled and papered copy. The survey questionnaire is shown in

Appendix A. As this study is to measure project managers’ perception of the knowledge

management practice in assisting project management success. Knowledge can be

categorised into Knowledge of Technical Solution, Knowledge of Organisational

38

Solution and Knowledge of Business Value (Reich et al., 2014). These three dimensions

consist of holistic measurement on knowledge management in project-based engineering

organisations. Perhaps, project management success can be measured in term of scope of

work, innovative design, project completion within budget, and project commissioning

within project schedule (Yeong & Lim, 2010). Several previous studies on knowledge

management adapted and adopted to design the questionnaire for this study.

Based on conceptual framework, multiple supporting dependent variables formed

primary dependent variable of the research which is “Project Management Success

Criteria”, as well as the multiple independent variable of the research is “Project-based

Knowledge”.

Survey questionnaire used to measure the perception of project managers in their passed

project experience. This questionnaire was comprehensively covering every dimensions

of project manager experience. The survey questionnaire with Five-Likert Scaling (1 =

Strongly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree) will be

used to measure the variables of knowledge management dimension. A categorical

measuring method (Yes or No) to be used to determine respondents perception on project

management success criteria. Respondents will be asked to indicate the degree of their

perspective on their knowledge on technical solution, organisational solution and

business value in their organisation and their project performance as a project team

members.

3.5 Sampling Procedures

PMI is one of the accredited bodies in Malaysia, which is the world’s leading not-for-

profit professional membership association for the project, program and portfolio

management profession. It founded in 1969 and delivers value for more than 2.9 million

professionals working in nearly every country in the world through global advocacy

(PMI, 2014).

39

PMI provided a name list consists of 150 project managers, project engineers or project

relevant team members for this study. 50 samples selected from the ages of 20 year old

to 30 year old, another 50 samples in the age of 31 year old to 40 year old, and another 50

samples selected from the age more than 51 year old. All sample must be serving at

Malaysian engineering organisation, either located in Malaysia or overseas. Based on the

name list, company of the respondents’ background should be studied to know the nature

of business; to make sure that project team members are from engineering company.

Survey form will be send through email or post to respondents. After two weeks from

the initial survey questionnaire released, two reminder emails will be sent to follow up on

the reply.

Ethics is an important practice and should be taken to protect respondents. Mainly, the

acceptability of respondents to provide information and perception to the researcher

needs to be respected. The researcher need to get the consent of the volunteer

respondents before survey to be conducted. However, respondents have right to

determine their willingness to answer to questionnaire (Liu, 2013). According to Liu

(2013), there are disputes of the respondents’ confidential and protection. Respondents’

details would be identified and released. Based on Sekaran & Bougie (2009) suggestion,

samples size which are larger than 30 and less than 300 are normally applicable to most

of the research.

3.6 Survey Instrumentation Description

The survey questions in Appendix A were adapted and adopted from literature review.

Literature review focused into the knowledge management contributed to project

management success criteria. These knowledge can be segregated into knowledge of

technical solution, knowledge of organisational solution and knowledge of business value

(Reich et al., 2014). The survey instrument contained of three sections. Section One of

the survey questionnaire indicated the biographical of the respondents.

40

Section Two of the survey questionnaire consisted of three types of project-based

knowledge. Type A of section two measured the knowledge of technical solution. These

consisted of eight questions to test on the understanding and importance of technical

knowledge to be applied in project-based organisations. In fact, the knowledge build up

from the project team members, who willing to create a learning ambient and share their

technical knowledge. According to Feo (2003), projects need technical knowledge to

execute the projects tasks. The systematic of knowledge stocking and knowledge

sharing mechanisms to be expected in working environment (Reich et al., 2004).

Researcher would expect the high degree of technical knowledge sharing and practices

would positively impact to the success of project management. Feo (2003) stated that

project-based organisations require three critical activities to managing the technical

knowledge. These are identification of critical knowledge (technical training, capture

project data, create deliverables), detection of knowledge sources (create technical

knowledge database) and validation of technical knowledge (providing standard

operating procedure). The main goal of technical knowledge management is to

encourage learning by providing projects with suitable knowledge. Conclusively, if

project team are encouraged to be more opportunities on technical sharing practice, then

the documents created by the project might be of better quality.

Type B of section two measured the knowledge of organisational solution. These

contained of six questions to test on the degree of organisational knowledge of the

respondents. Organisational knowledge create connection among division of

organisations (Feo, 2003). This enable the team to share information more effectively

with the key man of the organisations. Top management support is the key factor of the

implementation process. The tangible and intangible support can build up the project

team and overcome organisational barriers. Organisational assessment is important to be

consider for making changes across the department on project-based organisations. The

understanding of cross department among organisation can avoid an inconvenient

allocation of organisational resources and minimises the probability to create a culture

clash and create negative impact to members of the organisation (Feo, 2003).

41

Type C of section two focused on the business value knowledge owned by respondents.

There were four questions to be used. These questionnaires were adapted and adopted

from Lierni (2004), Reich et al. (2014), and Reich (2012). In the business context

knowledge, these capability measured from business strategy (efficiency and marketing

strategy), business culture (relationship) and learning capability (suitable solution) (Feo,

2003).

Section three of survey questionnaire contained of four criteria to measure the success of

project management. Question D1 used to measure the experience and understanding of

respondents on the criteria of scope of work of the involved projects. The factors of

failure of controlling the scope of work would be indicated in question D1a.

Question D2 used to measure the experience and understanding of respondents on the

criteria of controlling the project schedule of the involved projects. The factors of failure

of controlling the project schedule would be indicated in question D2a.

Question D3 used to measure the experience and understanding of respondents on the

criteria of quality of project to be delivered. The factors of failure of controlling the

quality of work would be indicated in question D3a.

The last criteria, question D4 used to measure the experience and understanding of

respondents on the criteria of cost handling of the involved projects. The factors of

failure of controlling the budget would be indicated in question D4a.

3.7 Data Analysis Techniques

IBM Statistics Package for the Social Sciences (SPSS) 22.0 as an analytical tool to

analyse the proposed hypotheses. After collecting data, researcher conducted a normality

and reliability test. Normality test is used to analyse a symmetrical, bell-shaped curve,

which has the greatest frequency of scores in the middle, with smaller frequencies

42

towards the extremes (Pallant, 2005). This test is based on assessment on skewness and

kurtosis values. The skewness value indicates the symmetry of the distribution A

positive skewness value means right skew; a negative means left skew, the greater the

absolute value, the greater the skew. Kurtosis value indicates the “peakedness” of the

distribution, positive kurtosis indicates that the distribution is rather peaked with long

thin tails, negative kurtosis value means the curve is relatively flat. If the distribution is

perfectly normal when skewness and kustosis value of zero.

There are few types of statistical method to assess reliability. One of the most common

method is analysis based on Cronbach’s alpha coefficient. Therefore Cronbach alpha test

is used to measure internal consistency of the instrument. Ideally, the Cronbach alpha

coefficient of a scale should be more than 0.7 (Pallant, 2005). According to Sekaran &

Bougie (2009), reliabilities less than 0.6 are considered to be poor, 0.7 are considered to

be acceptable and over 0.8 are considered to be good.

Table 1: Knowledge of Technical Solution Reliability Statistics

Item Mean Std Deviation N Cronbach’s Alpha N of Items KTS1 4.000 .67937 40

.819

8

KTS2 3.575 .93060 40 KTS3 3.675 .82858 40 KTS4 3.950 .55238 40 KTS5 3.900 .59052 40 KTS6 3.850 .69982 40 KTS7 3.750 .70711 40 KTS8 3.825 .67511 40

In terms of reliability the most important figure is the Alpha value. This is Cronbach’s

Alpha coefficient, which is .819 for knowledge of technical solution data. This value is

above .8, so the scale can be considered reliable with the sample.

43

Table 2: Knowledge of Organisation Solution Reliability Statistics

Item Mean Std Deviation N Cronbach’s Alpha N of Items KOS1 3.725 .67889 40

.845

6

KOS2 3.575 .81296 40 KOS3 3.850 .48305 40 KOS4 4.000 .55470 40 KOS5 3.625 .74032 40 KOS6 3.550 .71432 40

Cronbach’s alpha coefficient of knowledge of organisational solution data is .845. This

value is above .8, so the scale can be considered reliable with the sample.

Table 3: Knowledge of Business Value Reliability Statistics

Item Mean Std Deviation N Cronbach’s Alpha N of Items KBV1 3.825 .74722 40

.848

4 KBV2 3.925 .61550 40 KBV3 3.775 .73336 40 KBV4 3.975 .69752 40

Cronbach’s alpha coefficient of knowledge of business value data is .848. This value is

above .8, so the scale can be considered reliable with the sample.

Bivariate Correlation test shows the relationship between two variables in a linear

function (Coakes & Ong, 2011), as variable increases, the other also increase or as one

variable increases, the other variable decreases. A Pearson product-moment correlation

can be used to correlate a dichotomous and a continuous variable. Correlation between

two continuous variables is the most common measure of linear relationship. The

Pearson value correlation (r) can range from -1.00 to 1.00. This value will indicate the

strength of the relationship between two variables. A correlation of zero indicates no

relationship between the two variables. A correlation of 1.0 means a perfect positive

correlation, and a value of -1.0 means a perfect negative correlation. Cohen (1988) states

that r = .01 to .29 or r = -.01 to -.29 (weak relationship), r = .30 to .49 or r = -.3 to -.49

(medium strength relationship), r = .50 to 1.0 or r = -.50 to -1.0 (high strength

relationship) and summarised in table 4 (Pallant, 2005).

44

Table 4: Pearson Value Strength

Pearson Value, r Strength Relationship .01 to .29

-.01 to -.29 Weak

.3 to .49 -.3 to -.49

Medium

.05 to 1.0 -.05 to -1.0

High

The value indicates the strength of the relationship, while the sign (+ or -) indicates the

direction. There is a positive correlation when one variable increases, so too does the

other, negative correlation indicates that as one variable increases, the other decreases.

The size of the absolute value provides an indication of the strength of the relationship.

Each of the knowledge management dimensions will be tested with project success

measurement to conclude all hypotheses.

Multiple regression is an extension of bivariate correlation. The result of regression is an

equation that represents the best prediction of a dependent variable from several

independent variables. Regression analysis is used when independent variables are

correlated with one another and with the dependent variable. Independent variables can

be either continuous or categorical. For this study, project success is dependent variable

and knowledge management (Knowledge of technical solution, Knowledge of

organisational solution, and business value) are independent variables. The result of this

test will show the model of project success with three knowledge dimensions.

45

CHAPTER 4

RESEARCH RESULTS

This chapter describes the details of the data collected and output data from SPSS. The

purpose of this data is to answer the research questions in chapter 5. In order to answer

research questions, analysis test is required and results tabularised as below.

4.1 Frequency

The population of research consisted of project team members in Malaysia. In total of 40

respondents replied to the survey. Table 5 shows that there are 29 males (72.5%)

respondents and 11 female (27.5%) respondents in this survey.

Table 5: Frequency Table for Gender

Frequency (N) Percentage (%) Males 29 72.5 Female 11 27.5 Total 40 100

There are in the age range of 21 year old to 60 year old (shown in table 6). The largest

group of respondents’ ages of 21 year old to 30 year old (47.5%). This shows that

majority of young project team members willing respond to the survey questionnaire.

The second largest group of respondents’ ages fall between 31 year old and 40 year old

(37.5%). 12.5% of respondents in the ages ranges of 41 year old to 50 year old. Finally,

there is only 2.5% of respondent above 51 year old.

46

Table 6: Frequency Table for Age

Frequency (N) Percentage (%) 21 – 30 year old 19 47.5 31 – 40 year old 15 37.5 41 – 50 year old 5 12.5

51 year old and above 1 2.5 Total 40 100.0

Table 7 shows the year of participants’ experience in this survey. There are 72.5% of

respondents have undergone less than six years project management experience. 15% of

respondents have six to ten years project management experience. In the group of 11 to

20 years experiences respondents consist of ten percent of the total respondents.

Additionally, that is 1 respondent has 21 year experience in project management.

Table 7: Frequency Table for Years of Experience

Frequency (N) Percentage (%) Less than 6 years 29 72.5

6 - 10 year 6 15.0 11 – 20 year 4 10.0

21 year old and above 1 2.5 Total 40 100.0

Table 8 summarises that 47.5% of respondents perform as a project engineer and 20% as

a project manager. It follows by 12.5% of tender engineer. Besides that, ten percent of

respondents are top management of the project-based organisations. The rest of

respondents came from project executive and project sales personnel with 7.5% and 2.5%

respectively.

47

Table 8: Frequency Table for Job Category

Frequency (N) Percentage (%) Tender Engineer 5 12.5 Project Engineer 19 47.5 Project Executive 3 7.5

Project Sales Personnel 1 2.5 Project Manager 8 20.0 Top Management 4 10.0

Total 40 100.0

Table 9 summarises the respondents by industry. The largest group of respondents (40%)

came from construction industry. The other industries with the second and third largest

group of respondents were the environmental and automotive industries with 25% and

15% respectively. Besides that, ten percent respondents came from oil and gas industry.

It follows by five percent from electrical and instrumentation industry and 2.5% come

from power industry.

Table 9: Frequency Table for Industry Category

Frequency (N) Percentage (%) Automotive 6 15.0 Construction 16 40.0

Electrical & Instrumentation 2 5.0 Environment 10 25.0

Power 1 2.5 Oil & Gas 4 10.0

Others 1 2.5 Total 40 100.0

48

4.2 Tests of Normality

Normality data assessment is a prerequisite for many statistical tests. It is important for

underlying assumption for parametric testing. There are two type of assessment methods,

which are graphical method and numerical method.

Table 10: Test of Normality and Descriptive for Knowledge of Technical Solution,

Knowledge of Organisational Solution and Knowledge of Business Value

Variables Kolmogorov-Smirnova

Shapiro-Wilk Skewness Kurtosis

Statistic df Sig. Statistic df Sig. Statistic Std Error

Statistic Std Error

AVGKTS .174 40 .004 .932 40 .019 -.249 .374 .790 .733

AVGKOS .213 40 .000 .866 40 .000 -1.215 .374 1.531 .733

AVGKBV .240 40 .000 .850 40 .000 -.829 .374 2.398 .733

a: Lilliefors Significance Correction, AVGKTS: Knowledge of Technical Solution, AVGKOS: Knowledge of Organisational Solution,

AVGBV: Knowledge of Business Value

The skewness and kurtosis measures should be as close to zero as possible. Skewness z-

value of AVGKTS is -.666. This skewness z-value is in between -1.96 and 1.96.

Kurtosis z-value of AVGKTS is -1.077. This kurtosis z-value is in between -1.96 and

1.96. Since there are only 40 samples, the Shapiro-Wilk test is used. The p-value of

AVGKTS is .019 (P < .05). Ho is rejected, then data AVGKTS do not assume to be

normally distributed.

Skewness z-value of AVGKOS is -3.248. This skewness z-value is out of in between -

1.96 and 1.96. Kurtosis z-value of AVGKOS is 2.089. This kurtosis z-value is out of in

between -1.96 and 1.96. Since there are only 40 samples, the Shapiro-Wilk test is used.

The p-value of AVGKTS is .000 (P < .05). Ho is rejected, then data AVGKOS do not

assume to be normally distributed.

Skewness z-value of AVGKBV is -2.217. This skewness z-value is out of in between -

1.96 and 1.96. Kurtosis z-value of AVGKBV is 3.271. This kurtosis z-value is out of in

49

between -1.96 and 1.96. Since there are only 40 samples, the Shapiro-Wilk test is used.

The p-value of AVGKTS is .000 (P < .05). Ho is rejected, then data AVGKBV do not

assume to be normally distributed.

Inspection of the shape of the histogram provides information about the distribution of

scores on the continuous variables. In fact, the statistics show the variables are normally

distributed (shape of the normal curve), which most of the scores occurring in the centre,

tapering out towards the extremes. Figure 8, 9 and 10 further confirmed that these data

are not normally distributed.

Figure 8: Histogram for Knowledge of Technical Solution Data

50

Figure 9: Histogram for Knowledge of Organisational Solution Data

51

Figure 10: Histogram for Knowledge of Business Value Data

52

4.3 Bivariate Correlations

Bivariate correlations test on the relationship between independent variables and

dependent variables from conceptual framework. The research hypotheses below will

answer to the research questions and it would be discussed in chapter 5.

H1a) There is a significant relationship between knowledge of technical solution and

scope of work in project management.

Table 11: Descriptive Statistics for Knowledge of Technical Solution and Scope of Work

in Project Management

Mean Std. Deviation N AVGKTS 3.8156 .47619 40

PMSW 1.8500 .36162 40

Table 12: Correlations between Knowledge of Technical Solution and Scope of Work in

Project Management

AVGKTS PMSW AVGKTS Pearson Correlation 1 -.202

Sig. (2-tailed) .211 N 40 40

PMSW Pearson Correlation -.202 1 Sig. (2-tailed) .211

N 40 40

There are 40 samples in this study. The relationship between knowledge of technical

solution (as measured by the AVGKTS) and scope of work in project management (as

measured by the PMSW) was investigated using Pearson product-moment correlation

coefficient (r-value). The r-value of -.202 indicates the weak negative correlation

between knowledge of technical solution and scope of work in project management. The

53

p-value is .211, which is more than .05. That is not significant relationship between

knowledge of technical solution and scope of work in project management.

H1b) There is a significant relationship between knowledge of technical solution and

quality of the project.

Table 13: Descriptive Statistics for Knowledge of Technical Solution and Quality of the

Project


PMQ 1.9250 .26675 40

Table 14: Correlations between Knowledge of Technical Solution and Quality of the

Project

AVGKTS PMQ AVGKTS Pearson Correlation 1 -.238

Sig. (2-tailed) .139 N 40 40

PMQ Pearson Correlation -.238 1 Sig. (2-tailed) .139

N 40 40


solution (as measured by the AVGKTS) and quality of the project (as measured by the

PMQ) was investigated using Pearson product-moment correlation coefficient (r-value).

The r-value of -.238 indicates the weak negative correlation between knowledge of

technical solution and quality of the project. The p-value is .139, which is more than .05.

That is not significant relationship between knowledge of technical solution and quality

of the project.

54

H1c) There is a significant relationship between knowledge of technical solution and

controlling cost of the project.

Table 15: Descriptive Statistics for Knowledge of Technical Solution and Controlling

Cost of the Project


PMC 1.7000 .46410 40

Table 16: Correlations between Knowledge of Technical Solution and Controlling Cost

of the Project

AVGKTS PMC AVGKTS Pearson Correlation 1 .178

Sig. (2-tailed) .271 N 40 40

PMC Pearson Correlation .178 1 Sig. (2-tailed) .271

N 40 40


solution (as measured by the AVGKTS) and controlling cost of the project (as measured

by the PMC) was investigated using Pearson product-moment correlation coefficient (r-

value). The r-value of .178 indicates the weak positive correlation between knowledge of

technical solution and controlling cost of the project. The p-value is .271, which is more

than .05. That is not significant relationship between Knowledge of technical solution

and controlling cost of the project.

55

H1d) There is a significant relationship between knowledge of technical solution and


Table 17: Descriptive Statistics for Knowledge of Technical Solution and Project

Schedule Control

Mean Std. Deviation N AVGKTS 3.8156 47619 40

PMPS 1.7750 .42290 40

Table 18: Correlations between Knowledge of Technical Solution and Project Schedule

Control

AVGKTS PMPS AVGKTS Pearson Correlation 1 -.084

Sig. (2-tailed) .607 N 40 40

PMPS Pearson Correlation -.084 1 Sig. (2-tailed) .607

N 40 40


solution (as measured by the AVGKTS) and project schedule control (as measured by the

PMPS) was investigated using Pearson product-moment correlation coefficient (r-value).

The r-value of -.084 indicates the weak negative correlation between knowledge of

technical solution and project schedule control. The p-value is .607, which is more than

.05. That is not significant relationship between knowledge of technical solution and


56

H2a) There is a significant relationship between knowledge of organisational solution

and scope of work in project management.

Table 19: Descriptive Statistics for Knowledge of Organisational Solution and Scope of

Work in Project Management

Mean Std. Deviation N AVGKOS 3.7208 .50551 40

PMSW 1.8500 .36162 40

Table 20: Correlations between Knowledge of Organisational Solution and Scope of

Work in Project Management

AVGKOS PMSW AVGKOS Pearson Correlation 1 .373*

Sig. (2-tailed) .018 N 40 40

PMSW Pearson Correlation .373* 1 Sig. (2-tailed) .018

N 40 40 * Correlation is significant at the 0.05 level (2-tailed)

There are 40 samples in this study. The knowledge of organisational Solution helps to

explain nearly 13.9 percent of the variance in respondents’ scores on the success of scope

of work control in project management. The relationship between knowledge of

organisational solution (as measured by the AVGKOS) and scope of work in project

management (as measured by the PMSW) was investigated using Pearson product-

moment correlation coefficient. The r-value of .373 indicates the medium strength

positive correlation between knowledge of organisational solution and scope of work in

project management. The more organisational knowledge among project team, the

greater success of scope of work control in project management. The p-value is .018,

which is less than .05. That is significant relationship between knowledge of

organisational solution and scope of work in project management.

57

H2b) There is a significant relationship between knowledge of organisational solution

and quality of the project.

Table 21: Descriptive Statistics for Knowledge of Organisational Solution and Quality of

the Project


PMQ 1.9250 .26675 40

Table 22: Correlations between Knowledge of Organisational Solution and Quality of the

Project

AVGKOS PMQ AVGKOS Pearson Correlation 1 .063

Sig. (2-tailed) .701 N 40 40

PMQ Pearson Correlation .063 1 Sig. (2-tailed) .701

N 40 40

There are 40 samples in this study. The relationship between knowledge of

organisational solution (as measured by the AVGKOS) and quality of the project (as

measured by the PMQ) was investigated using Pearson product-moment correlation

coefficient (r-value). The r-value of .063 indicates weak positive correlation between

knowledge of organisational solution and quality of the project. The p-value is .701,

which is more than .05. That is not significant relationship between knowledge of

organisational solution and quality of the project.

58

H2c) There is a significant relationship between knowledge of organisational solution

and controlling cost of the project.

Table 23: Descriptive Statistics for Knowledge of Organisational Solution and

Controlling Cost of the Project


PMC 1.7000 .46410 40

Table 24: Correlations between Knowledge of Organisational Solution and Controlling

Cost of the Project

AVGKOS PMC AVGKOS Pearson Correlation 1 .362*

Sig. (2-tailed) .022 N 40 40

PMC Pearson Correlation .362* 1 Sig. (2-tailed) .022


There are 40 samples in this study. The knowledge of organisational solution helps to

explain nearly 13.1 percent of the variance in respondents’ scores on the success in

controlling cost of the project. The relationship between knowledge of organisational

solution (as measured by the AVGKOS) and controlling cost of the project (as measured

by the PMC) was investigated using Pearson product-moment correlation coefficient.

The r-value of .362 indicates the medium strength positive correlation between

knowledge of organisational solution and controlling cost of the project. The more

organisational knowledge among project team, the greater success of project management

in budget control. The p-value is .022, which is less than .05. That is significant

relationship between knowledge of organisational solution and controlling cost of the

project.

59

H2d) There is a significant relationship between knowledge of organisational solution

and project schedule control.

Table 25: Descriptive Statistics for Knowledge of Organisational Solution and Project

Schedule Control


PMPS 1.7750 .42290 40

Table 26: Correlations between Knowledge of Organisational Solution and Project

Schedule Control

AVGKOS PMPS AVGKOS Pearson Correlation 1 .358*

Sig. (2-tailed) .023 N 40 40

PMPS Pearson Correlation .358* 1 Sig. (2-tailed) .023


There are 40 samples in this study. The knowledge of organisational solution helps to

explain nearly 12.8 percent of the variance in respondents’ scores on the success of

project schedule control. The relationship between knowledge of organisational solution

(as measured by the AVGKOS) and project schedule control (as measured by the PMPS)

was investigated using Pearson product-moment correlation coefficient. The r-value of

.358 indicates the medium strength positive correlation between knowledge of

organisational solution and project schedule control. The more organisational knowledge

among project team, the greater success of project management in project schedule

control. The p-value is .023, which is less than .05. That is significant relationship

between knowledge of organisational solution and project management in project

schedule control.

60

H3a) There is a significant relationship between knowledge of business value and scope

of work in project management.

Table 27: Descriptive Statistics for Knowledge of Business Value and Scope of Work in

Project Management

Mean Std. Deviation N AVGKBV 3.8750 .58012 40

PMSW 1.8500 .36162 40

Table 28: Correlations between Knowledge of Business Value and Scope of Work in

Project Management

AVGKBV PMSW AVGKBV Pearson Correlation 1 .581**

Sig. (2-tailed) .000 N 40 40

PMSW Pearson Correlation .581** 1 Sig. (2-tailed) .000

N 40 40 ** Correlation is significant at the 0.01 level (2-tailed)

There are 40 samples in this study. The knowledge of business value helps to explain

nearly 33.8 percent of the variance in respondents’ scores on the success of scope of work

in project management. The relationship between knowledge of business value (as

measured by the AVGKBV) and scope of work in project management (as measured by

the PMSW) was investigated using Pearson product-moment correlation coefficient. The

r-value of .581 indicates the high strength positive correlation between knowledge of

business value and scope of work in project management. The more business value

knowledge among project team, the greater success of scope of work in project

management. The p-value is .000, which is less than .05. That is significant relationship

between knowledge of business value and scope of work in project management.

61

H3b) There is a significant relationship between knowledge of business value and quality

of the project.

Table 29: Descriptive Statistics for Knowledge of Business Value and Quality of the

Project


PMQ 1.9250 .26675 40

Table 30: Correlations between Knowledge of Business Value and Quality of the Project

AVGKBV PMQ AVGKBV Pearson Correlation 1 .104

Sig. (2-tailed) .525 N 40 40

PMQ Pearson Correlation .104 1 Sig. (2-tailed) .525

N 40 40

There are 40 samples in this study. The relationship between knowledge of business

value (as measured by the AVGKBV) and quality of the project (as measured by the

PMQ) was investigated using Pearson product-moment correlation coefficient (r-value).

The r-value of .104 indicates the weak positive correlation between knowledge of

business value and quality of the project. The p-value is .525, which is more than .05.

That is not significant relationship between knowledge of business value and quality of

the project.

62

H3c) There is a significant relationship between knowledge of business value and


Table 31: Descriptive Statistics for Knowledge of Business Value and Controlling Cost

of Project


PMC 1.7000 .46410 40

Table 32: Correlations between Knowledge of Business Value and Controlling Cost of

Project

AVGKBV PMC AVGKBV Pearson Correlation 1 .357*

Sig. (2-tailed) .024 N 40 40

PMC Pearson Correlation .357* 1 Sig. (2-tailed) .024



nearly 12.7 percent of the variance in respondents’ scores on the success of controlling

cost of project. The relationship between knowledge of business value (as measured by

the AVGKBV) and controlling cost of the project (as measured by the PMC) was

investigated using Pearson product-moment correlation coefficient. The r-value of .357

indicates the medium strength positive correlation between knowledge of business value

and controlling cost of the project. The more business value knowledge among project

team, the greater success of project management in budget control. The p-value is .024,

which is less than .05. That is significant relationship between knowledge of business

value and controlling cost of the project.

63

H3d) There is a significant relationship between knowledge of business value and project

schedule control.

Table 33: Descriptive Statistics for Knowledge of Business Value and Project Schedule

Control


PMPS 1.7750 .42290 40

Table 34: Correlations between Knowledge of Business Value and Project Schedule

Control

AVGKBV PMPS AVGKBV Pearson Correlation 1 .379*

Sig. (2-tailed) .016 N 40 40

PMPS Pearson Correlation .379* 1 Sig. (2-tailed) .016



nearly 14.4 percent of the variance in respondents’ scores on the success of project

schedule control. The relationship between knowledge of business value (as measured by

the AVGKBV) and project schedule control (as measured by the PMPS) was investigated

using Pearson product-moment correlation coefficient. The r-value of .379 indicates the

medium strength positive correlation between knowledge of business value and project

schedule control. The more business value knowledge among project team, the greater

success of project schedule control. The p-value is .016, which is less than .05. That is

significant relationship between knowledge of business value and project schedule

control.

64

Figure 11: Summary of Hypotheses Test

65

Table 35: Summary of Hypotheses Test

Item Hypotheses Result H1a There is a significant relationship between knowledge of

technical solution and scope of work in project management. Not Significant

H1b There is a significant relationship between knowledge of technical solution and quality of the project.

Not Significant

H1c There is a significant relationship between knowledge of technical solution and controlling cost of project.

Not Significant

H1d There is a significant relationship between knowledge of technical solution and project schedule control.

Not Significant

H2a There is a significant relationship between knowledge of organisational solution and scope of work in project management.

Significant

H2b There is a significant relationship between knowledge of organisational solution and quality of the project.

Not Significant

H2c There is a significant relationship between knowledge of organisational solution and controlling cost of project.

Significant

H2d There is a significant relationship between knowledge of organisational solution and project schedule control.

Significant

H3a There is a significant relationship between knowledge of business value and scope of work in project management.

Significant

H3b There is a significant relationship between knowledge of business value and quality of the project.

Not Significant

H3c There is a significant relationship between knowledge of business value and controlling cost of project.

Significant

H3d There is a significant relationship between knowledge of business value and project schedule control.

Significant

66

4.4 Results for Project Management

Table 36 summarises that there are 85% of respondents agree that project team has ability

to manage scope of work control. Besides that, 92.5% of respondents able to control

quality of the project. Additionally, 77.5% of respondents show their ability to control

project schedule. However, the lowest percentage of 70% respondents indicate their

ability to control cost of the project.

Table 36: Respondents Feedback on Ability to Management

Project Management Success Criteria

Respondent Agree on Ability to Manage

Respondent Disagree on Ability to Manage

Frequency Percentage Frequency Percentage Scope of Work Control

34 85.0 6 15.0

Control on the Quality of the Project

37 92.5 3 7.5

Control on the Cost of the Project

28 70.0 12 30.0

Control on the Project Schedule 31 77.5 9 22.5

4.5 Linear Regression Results

Table 37: Model Summary of Scope of Work Control as a Dependent Variable

Model R R Square Adjusted R Square

Std. Error of the Estimate

1 .704a .495 .453 .26741 a. Predictors (Constant), AVGKBV, AVGKTS, AVGKOS

Model summary from linear regression expands as following:

R, Multiple correlation coefficient = .704 (Indicates good prediction level)

R square, coefficient of determination = .495

67

This means 49.5% of the independent variables explains the variability of

dependent variable.

Table 38: ANOVA of Scope of Work Control as a Dependent Variable

Model Sum of Squares df Mean Square F Sig 1 Regression 2.526 3 .842 11.774 .000b Residual 2.574 36 .072 Total 5.100 39 b. Predictors: (Constant), AVGKBV, AVGKTS, AVGKOS

F-ratio shows whether the overall regression is a good fit for the data. The significant

level of .000 revealed that the independent variables is statistically significant in

predicting the dependent variable, F(3, 36) = 11.774, p < .05. Therefore, the regression

model is a good fit of the data. In other words, knowledge of technical solution,

knowledge of organisational solution and knowledge business value are able to predict

scope of work in project management significantly.

Table 39: Coefficients of Scope of Work Control as a Dependent Variable

Model Unstandardised Coefficients

Standardised Coefficients

t Sig. 95.0% Confidence

Interval for B B Std.

Error Beta Lower

Bound Upper Bound

1 (Constant) 1.288 .418 3.082 .004 .440 2.135 AVGKTS -.320 .095 -.421 -3.359 .002 -.513 -.127 AVGKOS .048 .112 .067 .430 .670 -.179 .276 AVGKBV .414 .098 .663 4.224 .000 .215 .612

Coefficient table descripts the following information:

For every degree of increment of scope of work control, there will be decreasing

of .421 degree of knowledge of technical solution.

For every degree of increment of scope of work control, there will be increasing

of .067 degree of knowledge of organisational value.

For every degree of increment of scope of work control, there will be increasing

of .663 degree of knowledge of business value.

68

If p < .05, meaning there is a statistically significant coefficient between the two

variables.

A multiple regression analysis was conducted to predict scope of work control from

knowledge of technical solution, knowledge of organisational solution and knowledge of

business value. It was found that knowledge of technical solution and knowledge of

business value statistical significantly predicted scope of work control, F(3, 36) = 11.774,

p < .05, R2 = .495. However, knowledge of organisational solution was not significant in

predicting scope of work control with p > .05 (significant level of .670).

Table 40: Model Summary of Quality Control as a Dependent Variable





R, Multiple correlation coefficient = .302



dependent variable.

Table 41: ANOVA of Quality Control as a Dependent Variable

Model Sum of Squares df Mean Square F Sig 1 Regression .253 3 .084 1.206 .322b Residual 2.522 36 .070 Total 2.775 39 b. Predictors: (Constant), AVGKBV, AVGKTS, AVGKOS


level of .322 revealed that the independent variables does not statistically significant in

predicting the dependent variable, F(3, 36) = 1.206, p > .05. In other words, knowledge

69

of technical solution, knowledge of organisational solution and knowledge business value

are unable to predict quality control in project management significantly.

Table 42: Coefficients of Quality Control as a Dependent Variable





Error Beta Lower

Bound Upper Bound

1 (Constant) 2.186 .414 5.286 .000 1.348 3.025 AVGKTS -.168 .094 -.300 -1.786 .082 -.359 .203 AVGKOS .023 .111 .044 .208 .837 -.202 .248 AVGKBV .076 .097 .165 .785 .437 -.120 .273


For every degree of increment of quality control, there will be decreasing of .300

degree of knowledge of technical solution.

For every degree of increment of quality control, there will be increasing of .044

degree of knowledge of organisational value.

For every degree of increment of quality control, there will be increasing of .165

degree of knowledge of business value.


variables.

A multiple regression analysis was conducted to predict quality control from knowledge

of technical solution, knowledge of organisational solution and knowledge of business

value. It was found that these variables did not statistical significantly predicted quality

control, F(3, 36) = 1.206, p > .05, R2 = .091.

Table 43: Model Summary of Cost Control as a Dependent Variable




70




This means 16% of the independent variables explains the variability of

dependent variable.

Table 44: ANOVA of Cost Control as a Dependent Variable



level of .095 revealed that the independent variables does not statistically significant in

predicting the dependent variable, F(3, 36) = 2.285, p > .05. In other words, knowledge

of technical solution, knowledge of organisational solution and knowledge business value

are unable to predict cost control in project management significantly.

Table 45: Coefficients of Cost Control as a Dependent Variable





Error Beta Lower

Bound Upper Bound

1 (Constant) .135 .692 .195 .847 -1.268 1.538 AVGKTS .053 .158 .055 .338 .738 -.266 .373 AVGKOS .199 .186 .217 1.072 .291 -.177 .575 AVGKBV .160 .162 .201 .990 .329 -.168 .489


For every degree of increment of cost control, there will be increasing of .055

degree of knowledge of technical solution.


degree of knowledge of organisational value.

71


degree of knowledge of business value.


variables.

A multiple regression analysis was conducted to predict cost control from knowledge of

technical solution, knowledge of organisational solution and knowledge of business

value. It was found that these variables did not statistical significantly predicted cost

control, F(3, 36) = 2.285, p > .05, R2 = .160.

Table 46: Model Summary of Project Schedule Control as a Dependent Variable








dependent variable.

Table 47: ANOVA of Project Schedule Control as a Dependent Variable



level of .029 revealed that the independent variables is statistically significant in

predicting the dependent variable, F(3, 36) = 3.352, p < .05. Therefore, the regression

72

model is a good fit of the data. In other words, knowledge of technical solution,

knowledge of organisational solution and knowledge business value are able to predict

project schedule control in project management significantly.

Table 48: Coefficients of Project Schedule Control as a Dependent Variable





Error Beta Lower

Bound Upper Bound

1 (Constant) 1.018 .608 1.675 .103 -.215 2.253 AVGKTS -.216 .138 -.243 -1.559 .128 -.497 .065 AVGKOS .198 .163 .236 1.211 .234 -.133 .528 AVGKBV .218 .142 .299 1.530 .135 -.071 .507


For every degree of increment of project schedule control, there will be

decreasing of .243 degree of knowledge of technical solution.

For every degree of increment of project schedule control, there will be increasing

of .236 degree of knowledge of organisational value.

For every degree of increment of project schedule control, there will be increasing

of .299 degree of knowledge of business value.


variables.

A multiple regression analysis was conducted to predict cost control from knowledge of

technical solution, knowledge of organisational solution and knowledge of business

value. It was found that these variables did not statistical significantly predicted project

schedule control, F(3, 36) = 3.352, p > .05, R2 = .218.

73

4.6 Failure Factor Results

There are survey on the factor of failure on project management. Even though these are

minority response. However, these factors of failure on project management, which

shown in table 49, need to be carefully analyse from the respondent in order to improve

project management. Many respondents agree that project team did not clearly

understand on the delivery scope is the main factor of failure in scope of work control.

Miscommunication between project team and procurement team is the second highest

ranking of failure factor. Besides that the factors follow by “mistake in proposal”,

“undocumented in minute of meeting”, “misunderstanding during the design” located in

the ranking or third, fourth, and fifth respectively. The last three factors will be “unclear

documented in minutes of meeting”, “unclear quotation to clients”, and “insufficient of

information from client during preliminary stage” respectively.

Table 49: Failure Factors on Scope of Work Control

Failure Factors Weightage Ranking Misunderstanding during the design 4 5 Insufficient of information from client during preliminary stage

1 8

Unclear quotation to clients 2 7 Mistake in proposal 6 3 Unclear documented in minutes of meeting 3 6 Undocumented in minute of meeting 5 4 Miscommunication between project team and procurement team

7 2

Project team did not clearly understand on the deliverable scope

8 1

In order to understand the factor of failure on project quality control, the feedback from

respondents can be considered as shown in table 50. The main factor will be

miscommunication between project team and procurement team. At second highest

ranking of factor is cutting corner in design and it follows by tolerance of QA/QC team

and unqualified suppliers or sub-contractors. The least impact factor will be tolerance of

project team.

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Table 50: Failure Factors on Controlling the Quality of Project

Failure Factors Weightage Ranking Tolerance of project team 1 5 Unqualified suppliers or sub-contractors 2 4 Tolerance of QA/QC team 3 3 Cutting corner in design 4 2 Miscommunication between project team and procurement team

5 1

Table 51 tabulated the ranking of failure factors on project cost control. Majority of

respondents highlighted the delay in project period would be the main factor. The second

ranking to be blamed on procurement team do not source for more suppliers. The third

ranking belong to the factor of unable to get competitive price from supplier due to

frequent delay in payment. Fourth and fifth failure factor would be less of suppliers

contacts and unhealthy in vendor system respectively. The last two factors would be

project manager unable to control the expenses within project team and under quote

during proposal stage.

Table 51: Failure Factors on Controlling the Cost of the Project

Failure Factors Weightage Ranking Under quote during proposal stage 1 7 Project manager unable to control the expenses within project team

2 6

Unhealthy in vendor system 3 5 Less of suppliers contacts 4 4 Unable to get competitive price from supplier due to frequent delay in payment

5 3

Procurement team do not source for more suppliers 6 2 Delay in project period 7 1

There are twelve failure factors on project schedule control as listed in table 52. Most of

the respondents highlighted that “project manager did not track closely on the project

progress” is the key factor of the delay of the project. Another significant factor of

failure would be additional jobs scope to be added during project progress.

Miscommunication between project team and procurement team is another roof factor of

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the failure in controlling the project schedule. “Long procedure in giving approval from

client”, “delay in approval from authorities”, “design team took longer time in design”,

and “long procedure in purchasing” would be the fourth, fifth, sixth and seventh ranking

factor respectively. It follows by the factor of project team spends a longer time to

source for purchased products and the project manager unable to dedicate tasks

effectively. The less critical factors will be “the project manager unable to effectively

resolve issues”, “the project manager unable to effectively communicate with other

parties”, and “uncertainty on the purchased product lead time”.

Table 52: Failure Factors on Controlling the Project Schedule

Failure Factors Weightage Ranking Uncertainty on the purchased product lead time 1 12 The project manager unable to effectively communicate with other parties

2 11

The project manager unable to effectively resolve issues 3 10 The project manager unable to dedicate tasks effectively 4 9 Project team spends a longer time to source for purchased products

5 8

Long procedure in purchasing 6 7 Design team took longer time in design 7 6 Delay in approval from authorities 8 5 Long procedure in giving approval from client 9 4 Miscommunication between project team and procurement team

10 3

Additional jobs scope to be added during project progress 11 2 Project manager did not track closely on the project progress

12 1

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CHAPTER 5

DISCUSSION AND CONCLUSION

Chapter 5 discusses the findings in terms of research questions and corresponding

hypotheses and a summary of research contributions of this research. It discusses the

limitations of the research project based on research design considerations. Then

proposes a detailed scope of research in the future.

5.1 Discussion

This research applies to determine if there is a relationship between project-based

knowledge and project management success criteria. The research focuses on the

knowledge management practices in use in project-based organisations in order to

improve project management applications. This study provide the contribution of

knowledge management towards project management. A desired output of the research

is to encourage the implementation of knowledge management practice in project-based

organisations and benefit to project stakeholders, such as project clients, project team

members, authorities and societies.

The conclusions for this research were based on 95% or greater confidence level due to

the sample size and the anticipated response rate. In total, there were 40 respondents to

the survey questionnaire. The thoughtfulness of the respondents towards the purpose of

the study is proven by the number of responses to the survey questions as shown in

Chapter 4, Research Results, where the number of responses is greater than the

77

statistically acceptable n more than 30 (Lierni, 2004). When n more than 30, the

sampling distribution of the β is approximately normal. (Lierni, 2004)

Based on the responses from this survey, majority of respondents are young project team

members, which 47.5% respondents from the age group from 21 year old to 30 year old.

They feel comfortable to undertake this survey. From the prospective of proactively

participated in the survey, they may have more time and care about taking advantage of

an opportunity to make their own contribution to the knowledge base of project

management by sharing their own experience with using knowledge sharing and project

management in their own projects.

Among a project team, project engineer is majority in a team, therefore, more project

engineers participated in this research survey. Then followed by project manager. The

rest of project team members are tender engineer, project executive, project sales

personnel and top management of project-based organisations. This research has taken

samples from varies industries of project-based organisations, including automotive,

construction, electrical and instrumentation, Environment, power, and oil and gas.

Majority respondents came from construction industry. This is justified that Malaysia is

undergoing a development stage, construction industry is actively grown in current

situation. Besides that, environmental industry is required for environmental assessment

and provide environmental facilities. Therefore, environmental industry respondents

were the second largest group of respondents.

Research Question a:

What are the contribution of knowledge management towards project management?

The results of the contribution was summarised in figure 11 of chapter 4.4, the

hypotheses tested by using bivariate correlation test. Result showed that none of

knowledge of technical solution contributes to the project management success. Even

though technical knowledge may be essential to project management success, but

research showed that it does not significant to project management success. According to

Langer et al, tacit knowledge of organisational culture and clients are the most significant

contribution to project management. This soft skill will indirectly improve to the project

78

management via complexity coordination with client especially while dealing with less

familiarity project.

There is significant relationship between knowledge of organisational solution and scope

of work control. Organisational solution knowledge includes skills changes and culture

changes give support to project team to control the scope of work. This knowledge

should cooperate among organisation. Understanding operation of each department.

This cooperation should include project department with sales department and purchasing

department. The alliances between there three department will build up a stronger project

team, who has better understanding on scope of work to be offered. These will be further

confirmed the product or services offered can solve client’s existing problems.

The scope of work control will be directly impact on cost and project schedule control.

Clements et al. (2012) also emphasis that scope of work control will affect to project

budget and schedule.

The result of survey also state that there is significant relationship between knowledge of

business value and scope of work control. Business value knowledge refers to the

understanding of business objectives. This knowledge is important to deliver the most

suitable product and services to client. At the very beginning stage, business object must

be plant among project team members. They need to share same ultimate goal in order to

deliver solution to client. Furthermore, scope of work control will share impact to cost

and schedule control.

Research Question b:

How to relate project-based knowledge categories to success project management

criteria?

Linear regression test to be used to find out the relationship of the project-based

knowledge categories to success project management criteria. Survey result show that

the only one model of relationship can be justified. That is scope of work control is

negatively related to knowledge of technical solution with the coefficient of .421; and

there is positively related to knowledge of business value with the coefficient of .663.

These mean the improvement of technical knowledge will reduce the scope of work

79

control. However, business value knowledge will be improve the scope of work control.

Indirectly, the improvement of scope of work control will contribute positive impact to

budget and project schedule control. The improvement of technical knowledge may

create personal ergo. This scenario can be inference from the response rate of the survey.

Majority of respondents are below 30 year old. Egoism among the team will break down

the communication among project team members.

Research Question c:

What are the factors of implementation knowledge management in success project?

As known, knowledge management is important to be implemented in order to manage

project successively. However, it take time for project team members to understand the

appropriate methods to start up the project management in the most effective ways. The

knowledge selection and sharing will be a big challenge to implement knowledge

management. Project-based organisation need to select and store the useful data in

become knowledge database. This require Information Technology (IT) assistance, this

is an important for organisations to invest in IT. In order to select and store projects data

into a database, contribution of knowledge among the organisational level become an

important moves. From the bivariate correlation result of knowledge of organisational

solution, it justified that organisational support is a key factor in implementation of

knowledge management in project-based organisations. Organisational knowledge

should come from the sharing of leadership, training, clear business strategy, sharing of

business goal, department collaboration. There are very difficult for different segment of

team members to share their knowledge to all project team members in an organisation.

Different segment of staffs in an organisation do not often meet and talk together, and

there are communication barrier across the department or within the department.

Therefore, encoding and decoding of knowledge for every level of staffs become a key

media to contribute their knowledge. The role of leadership is important to be planted in

every level of staffs. Every level of staffs should have initiated to share their knowledge

to other colleagues. Other than knowledge sharing, training is required to equip staffs.

Lack of knowledge will cause the failure in identifying knowledge. Project team

members do not know what to do in sorting the knowledge data and how to apply the

existing knowledge.

80

Research Question d:

What are the difficulties of execution knowledge management in engineering companies?

Based on the feedback collected, the main difficulty of executing knowledge

management is human related challenge (Ou & Davison). They may be busy with pile of

works until they ignore the impact of knowledge sharing. As junior workers expressed

the willingness to knowledge sharing. However, junior workers lack of knowledge to be

shared. Therefore, knowledge management implementation difficulty should be studied

through creation of explicit knowledge, knowledge storage, transfer and application.

This result has been supported by the research from Ou & Davison, this report shows that

the difficulty of knowledge management can be classified into three aspects, such as

structural related causes, human related causes and technical related causes (Ou &

Davison). Most of the organisations do not create the culture to encourage knowledge

creation and sharing. The organisation does not provide knowledge management system

properly. It takes time for junior project team members to catch up best practices. Senior

staffs may not be willing to share their knowledge and problem solving skill. They may

afraid of losing competitive in the organisation after sharing their knowledge. Ou and

Davison also mentioned that the personal relationship (guanxi) is a factor obstacle of

knowledge sharing. The IT system on knowledge management does not facilitate the

movement of knowledge management practices. Some organisations are still using the

non-usefulness of knowledge management systems.

5.2 Research Implication

Knowledge management need to be properly planned to be executed in organisation. As

known, knowledge creation is the most initial stage to implement knowledge

management. A success factor in knowledge management practice must be focus on how

an organisation creates internal communications among different departments in order to

strengthen organisational knowledge base. The recognition of internal communications

81

across department are necessary. In fact, communication encoding and decoding will

become a future study area. The effective of communication among the organisation will

be the success factor of knowledge management planning. In future, method of encoding

and decoding need to be deeply study. It may involve in IT applications. The cross over

scope between IT industry and social science research must be encouraged to examine

the mechanism of knowledge creation, sharing, transfer and application.

5.3 Limitation of Research

The perception of junior staffs is different from the senior position workers in the

understanding of the knowledge management practice within an organisation. This

research survey respondents mostly are junior staffs, this may not be able to understand

the actual mind set of senior or experienced staffs.

The statistical results in correlation bivariate test shows that most of the relationships are

at the weak and medium strength level. These results do not able to provide a

comprehensive explanation on relationship between independent variables and dependent

variables.

5.4 Recommendations

This research samples collected from 150 project management personnel in engineering

organisations. A bigger sample size need to be collected to deliver a comprehensive

knowledge management contribution to project-based organisations. A stronger design

would use a matched sample of project-based personnel so that the independent and

dependent data are collected from bigger group to improve the sample size.

A case study on engineering organisation will be able to narrow down the impact of

knowledge management toward project management. The operation knowledge

82

management in an organisation would affect the finding of the research. Therefore, a

combination of survey and interview data collection is required to improve the research

findings.

5.5 Conclusion

For a project to be successful, it's not enough simply to manage the project competently,

and deliver a good quality product and services. Based on the respondent feedback,

project failure mainly caused by human factor. Therefore, to avoid failure, knowledge of

organisational solution and knowledge of business value need to be identified and shared

among the staffs. Result of survey shows that both knowledge of organisational solution

and knowledge of business value are significantly positive relationship with scope of

work control, cost control, and project schedule control. Besides that, knowledge of

technical solution and knowledge of business value statistical significantly predicted

scope of work control, F(3, 36) = 11.774. Junior project members are very keen to learn

knowledge through knowledge management platform. Project-based organisation can

emphases on leadership skill while implement knowledge management among project-

based organisation.

83

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Appendix A

UNIVERSITI TUNKU ABDUL RAHMAN (UTAR) FACULTY OF ACCOUNTANCY AND MANAGEMENT

Dear Participant,

I am a MBA student in the Faculty of Accountancy and Management (FAM) at Universiti Tunku Abdul Rahman and I am conducting a research of "The Contribution of Knowledge Management to Project Management Performance in Engineering Project-Based Organisations". This research aims to deliver the following objectives:

a) Find out the contribution of knowledge management towards project management

b) Find out the relationship of project based knowledge categories to success project management criteria.

c) The factor of implementation knowledge management in success project

d) The difficulties of execution knowledge management in engineering company

Through your participation, I eventually hope to justify the relationship of knowledge management and project management. This study may provide a clearer picture on implementation of knowledge management in project oriented organisation.

It may take 15 to 20 minutes to look through and complete the questionnaire by followed the given instructions, then click “submit” at the last page of the questionnaire. Participation is strictly voluntary and you may refuse to participate at any time. Your responses will not be identified and your answers will not influence your present or future employment.

Thank you for taking the time to assist me in my educational endeavors. Completion and return of the questionnaire will indicate your willingness to participate in this study. If you require additional information or have questions, please contact me at +6012-808 5980 or at [email protected]. If you have any questions about your rights as a research subject, you may contact the Institute of Postgraduate studies and Research of Universiti Tunku Abdul Rahman (UTAR) by mail at 13 Jalan 13/6, 46200 Petaling Jaya, Selangor Darul Ehsan, or by phone at 603-7958 2628 Ext 8202 / 8204, or by email at [email protected]

Kindly click on the link to start your survey: https://www.surveymonkey.com/s/utarmba1105998 Thank you very much. Sincerely, Francis Nee Francis Nee Master of Business Administration Student Universiti Tunku Abdul Rahman (UTAR)

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SECTION ONE

PERSONAL BACKGROUND You are invited to participate in a survey which relevant to project management and knowledge management. Any answers you give will remain confidential to the researcher and will be used only for research purposes in academic publications. Your privacy is important. INSTRUCTION: Please mark ( √ ) at the relevant spaces next to the question in which the answers that are more applicable for you. 1. Gender [ ] Male [ ] Female 2. Age ________ years old 3. Race [ ] Malay [ ] Native [ ] Chinese [ ] Indian [ ] Other, please specify ______________________ 4. Marital Status [ ] Married [ ] Single [ ] Divorced [ ] Widowed 5. Education Level [ ] SPM [ ] STPM or Certificate [ ] Diploma [ ] Degree [ ] Master [ ] Doctoral [ ] Others, please specify _____________________ 6. Years of Experience in Project Management ________ years 7. Monthly Income [ ] Less than RM2,000 [ ] RM2,001 – RM3,000 [ ] RM3,001 – RM4,000 [ ] RM4,001 – RM5,000 [ ] RM5,001 – RM7,000 [ ] RM7,001 – RM10,000 [ ] RM10,001 – RM15,000 [ ] More than RM15,001 8. Job Category [ ] Tender Engineer [ ] Project Engineer [ ] Project Executives [ ] Project Sales Personnel [ ] Project Manager [ ] Top Management [ ] Others, please specify _____________________ 9. Company Category [ ] Automotive [ ] Construction [ ] Electrical & Instrumentation [ ] Environmental

[ ] Power [ ] Oil & Gas [ ] Others, please specify _____________________

NEXT PAGE Page 2 of 6

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SECTION TWO INSTRUCTION: Read each question carefully and then circle an answer which you feel reflects your judgment by using the following scale:

1 2 3 4 5 Strong Disagree Disagree Neutral Agree Strongly Agree

A KNOWLEDGE OF TECHNICAL SOLUTION

A1. Project teams create deliverables, including any new information and technical solution learned on the project, which can be used by the firm in the future

1 2 3 4 5

A2. Ease to search for technical data in the organisation (Does not include internet browsing)

1 2 3 4 5

A3. The organisation has the ability to provide necessary technical training to those on project that need it

1 2 3 4 5

A4. Information such as project / subordinate plans and project results that goes into the database is standardized so that project data needed on future projects can be easily retrieved by those that need it

1 2 3 4 5

A5. The organisation has the ability to capture project data for use during conduct of the project and after the project has been completed

1 2 3 4 5

A6. The organisation has clearly provided the standard operating procedure of the project management to project team

1 2 3 4 5

A7 There have a standard compilation of databases that are given to all new hires

1 2 3 4 5

A8 The organisation has provided useful technical databases for

project team 1 2 3 4 5


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B KNOWLEDGE OF ORGANISATIONAL SOLUTION

B1. The organisation provides the project team with necessary financial resources needed

1 2 3 4 5

B2. The organisation provided the projects team with necessary people needed

1 2 3 4 5

B3. The organisation provided the projects team with information needed

1 2 3 4 5

B4. The organisation provided the projects team with the necessary facilities / workspace / equipment needed

1 2 3 4 5

B5. The organisation has the ability to define skills and knowledge needed by those implementing the strategy

1 2 3 4 5

B6. The organisation has the ability to select a project team with the required skills and competencies necessary to execute projects

1 2 3 4 5

C

KNOWLEDGE OF BUSINESS VALUE

C1. The organisation responds to client needs in a timely and effective manner

1 2 3 4 5

C2. The organisation exhibits a drive for results and deliver what was needed by client

1 2 3 4 5

C3. The organisation pursues marketing strategies to maintenance the relationship with clients

1 2 3 4 5

C4. The organisation keep good relationship with suppliers and sub-contractors

1 2 3 4 5


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D PROJECT MANAGEMENT D1. The organisation has ability to control the scope of work

[ ] Yes (Go to Question D2) [ ] No (Go to Question D1a)

D1a. The changes of scope of work due to (You can rate more than 1 choice): Rate the applicable factors only, 1 for minor factor and 8 for major factor [ ] Misunderstanding during the design [ ] Insufficient of information from client during preliminary stage [ ] Unclear quotation to clients [ ] Mistake in proposal [ ] Unclear documented in minutes of meeting [ ] Undocumented in minute of meeting [ ] Miscommunication between project team and procurement team [ ] Project team did not clearly understand on the deliverable scope

D2. The organisation has ability to control the project schedule [ ] Yes (Go to Question D3) [ ] No (Go to Question D2a)

D2a. The delay of project due to (You can rate more than 1 choice):

Rate the applicable factors only, 1 for minor factor and 12 for major factor [ ] Uncertainty on the purchased product lead time [ ] The project manager unable to effectively communicate with other parties [ ] The project manager unable to effectively resolve issues [ ] The project manager unable to dedicate tasks effectively [ ] Project team spends a longer time to source for purchased products [ ] Long procedure in purchasing [ ] Design team took longer time in design [ ] Delay in approval from authorities [ ] Long procedure in giving approval from client [ ] Miscommunication between project team and procurement team [ ] Additional jobs scope to be added during project progress [ ] Project manager did not track closely on the project progress


95

D3. The organisation has ability to control the quality of deliverable products [ ] Yes (Go to Question D4) [ ] No (Go to Question D3a)

D3a. The failure of controlling the quality due to (You can rate more than 1 choice):

Rate the applicable factors only, 1 for minor factor and 5 for major factor [ ] Tolerance of project team [ ] Unqualified suppliers or sub-contractors [ ] Tolerance of QA/QC team [ ] Cutting corner in design [ ] Miscommunication between project team and procurement team

D4. The organisation has ability to control the cost of project [ ] Yes (The End) [ ] No (Go to Question D4a)

D4a. The failure of controlling the project cost due to (You can rate more than 1 choice):

Rate the applicable factors only, 1 for minor factor and 7 for major factor [ ] Under quote during proposal stage [ ] Project manager unable to control the expenses within project team [ ] Unhealthy in vendor system [ ] Less of suppliers contacts [ ] Unable to get competitive price from supplier due to frequent delay in payment [ ] Procurement team do not source for more suppliers [ ] Delay in project period

~ Thank you for your time and efforts ~

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